DevOps & CI/CD MCP Servers

Tools to read, search, and manipulate Git repositories. Full Git operations support.

The GitHub MCP server is GitHub's official Model Context Protocol integration, giving AI assistants like Claude and Cursor direct, authenticated access to the GitHub platform and its full developer surface. With this MCP server, you can ask your AI to read and write repository files, create and merge branches, open and review pull requests, comment on and close issues, trigger GitHub Actions workflows, search across code repositories with GitHub's code search, and inspect commit history — all through natural-language prompts in your AI interface. Developers use it to supercharge code review workflows, automate issue triage, generate PR descriptions from diffs, bulk-update repository settings, and wire AI agents into CI/CD pipelines. The GitHub MCP server connects via a GITHUB_PERSONAL_ACCESS_TOKEN environment variable with scopes for the operations you need, keeping authentication clean and auditable. Install with Docker: `docker run -e GITHUB_PERSONAL_ACCESS_TOKEN=<token> ghcr.io/github/github-mcp-server` — or configure it as a remote MCP server in Claude Desktop, Cursor, VS Code, Windsurf, and Cline. With over 8,000 GitHub stars, it is the most widely deployed official code-platform MCP server and the reference implementation for AI-native GitHub automation.

GitLab's official MCP server enabling AI tools to securely access GitLab project data, manage issues, and perform repository operations via OAuth 2.0.

AWS Labs maintains a monorepo of specialized, open-source MCP servers that bring AWS best practices directly into AI-assisted development workflows, spanning infrastructure, data, AI/ML, cost management, and healthcare/life-sciences domains. Rather than one monolithic server, the project ships dozens of focused servers you install individually depending on the task: the AWS Documentation MCP Server for real-time official docs and API references, dedicated servers for Terraform/CDK/CloudFormation infrastructure-as-code, container and serverless platforms (ECS, EKS, Lambda), SQL/NoSQL databases (DynamoDB, RDS, Aurora), search and analytics (OpenSearch), messaging (SQS/SNS), and cost/billing analysis. Most servers install via uvx with a package name like awslabs.aws-documentation-mcp-server, run locally over stdio, and use standard AWS credential chains (IAM roles, profiles, or access keys) rather than exposing raw account credentials to the model. AWS also now offers a managed, remote "AWS MCP Server" (in preview) that combines full API coverage with pre-built agent SOPs, syntactically validated API calls, and complete CloudTrail audit logging for teams that want centralized governance instead of running servers locally. The Getting Started with Kiro/Cursor/VS Code/Claude Code sections in the repo provide one-click install configs for each server, making it straightforward to wire up only the AWS services a given project actually touches.

Cloudflare's official mcp-server-cloudflare repo ships 13+ remote, domain-specific MCP servers rather than one monolith — Documentation, Workers Bindings (storage/AI/compute primitives), Workers Builds, Observability (logs/analytics), Container sandboxes, Browser Rendering (fetch pages, convert to markdown, screenshots), Logpush health, AI Gateway (prompt/response search), Audit Logs, DNS Analytics, Digital Experience Monitoring, Cloudflare One CASB, and GraphQL analytics, each hosted at its own `*.mcp.cloudflare.com/mcp` endpoint over Streamable HTTP (SSE is deprecated but still supported). For broad, code-execution-style access across many Cloudflare products at once, Cloudflare separately publishes a Code Mode server at mcp.cloudflare.com (repo: cloudflare/mcp) — pick domain-specific servers when you want curated, typed tools for one product area (e.g. just Workers or just DNS), and Code Mode when you want fewer, more general-purpose tools. Clients without native remote-MCP support connect via `npx mcp-remote https://<subdomain>.mcp.cloudflare.com/mcp` in their config; clients like the Cloudflare AI Playground accept the URL directly. OpenAI Responses API integration is also documented, requiring a scoped Cloudflare API token per server (e.g. Browser Rendering needs specific dashboard-generated permissions). Typical use: "show me why my Worker is erroring" pulls real-time observability data, or "summarize this URL" drives the Browser Rendering server to fetch and convert a live page to markdown.

The Vercel MCP server is a powerful Model Context Protocol integration that allows AI assistants like Claude, Cursor, and Cline to interact directly with your Vercel infrastructure. It exposes essential platform capabilities as AI-callable tools, meaning you can manage projects, trigger deployments, inspect build logs, and configure custom domains via natural language prompts. For frontend developers and DevOps teams working within the Vercel ecosystem, this eliminates the need to constantly context-switch between an IDE, terminal, and the Vercel dashboard. You can simply ask your AI agent to "check the status of the latest production deployment", "fetch the build logs for the staging environment and identify the Next.js hydration error", or "list all environment variables for the current project". By bridging the gap between your codebase and your hosting platform, the Vercel MCP server turns your AI assistant into an embedded DevOps engineer capable of diagnosing build failures and managing serverless deployments in real time. Vercel ships this as an official hosted (remote) MCP server at https://mcp.vercel.com — there is no package to install locally. Connect an MCP client to that URL and authenticate through the browser-based OAuth flow, which scopes access to the Vercel teams and projects your account can already reach rather than a long-lived Personal Access Token. For example, add it to Claude Code with `claude mcp add --transport http vercel https://mcp.vercel.com`, then complete the OAuth consent screen; the repo vercel/vercel-mcp-overview is the official public overview of this server, with full docs at vercel.com/docs/mcp/vercel-mcp.

The Docker MCP server connects your AI assistant directly to your local or remote Docker daemon, exposing container lifecycle management and image orchestration as Model Context Protocol tools. With this integration, developers can prompt Claude, Cursor, or Windsurf to inspect running containers, view real-time logs, build new images from Dockerfiles, start and stop services using Docker Compose, and prune unused system resources through natural language. Rather than switching to a terminal to type complex docker inspect commands, you can simply ask your AI to "find out why the postgres container keeps crashing" or "tail the last 100 lines of the frontend container logs and find the React error". This is a game-changer for DevOps engineers, backend developers, and system administrators who want to streamline container debugging, automate compose cluster orchestration, and troubleshoot networking issues faster. The server interacts securely with the Docker Engine API, meaning it can both read system state and execute commands like port binding or volume inspection. It works cross-platform wherever Docker Desktop or the Docker daemon is running. Docker's official implementation ships as the Docker MCP Gateway (docker/mcp-gateway), a `docker mcp` CLI plugin that acts as a single secure gateway in front of many containerized MCP servers from the Docker MCP Catalog — each downstream server runs in its own isolated container with resource limits and secret injection, so an assistant connects once to the gateway instead of wiring up dozens of individual servers. Start it with `docker mcp gateway run`, then point Claude Desktop, Cursor, or another client at the gateway; `docker mcp server enable <name>` toggles which catalog servers (including the Docker/container-management tools) are exposed. This container-per-server isolation is the key security benefit over running MCP servers directly on the host.

The Kubernetes MCP server (mcp-server-kubernetes, built by Flux159) brings cluster management capabilities into AI assistant workflows, letting developers and platform engineers query and manage Kubernetes resources through natural-language interactions with Claude, Cursor, and other MCP-compatible clients. It loads your existing kubeconfig automatically, so it works with any cluster — local minikube and kind setups, Amazon EKS, Google GKE, Azure AKS, or on-premises deployments — with no separate credential setup required. Core tools exposed by the server include: listing pods, deployments, services, and namespaces; describing individual resources and their status; fetching pod logs for debugging; applying and updating manifests; scaling deployments; checking rollout status and history; and querying resource utilization and cluster events. A built-in non-destructive mode can disable delete/scale-down operations entirely, making it safe to point at production clusters for read-only diagnostics. DevOps engineers use it to debug failing deployments by asking Claude to inspect pod logs and recent events, identify resource constraints causing OOMKilled pods, or summarize the current state of a namespace before a production release. For SREs responding to incidents, it enables rapid triage through conversational commands — no memorizing kubectl flags or switching terminal windows mid-incident — and optional OpenTelemetry integration adds observability into what the AI agent actually did against the cluster. Install with: `npx mcp-server-kubernetes`. Pairs well with the GitHub MCP server for full GitOps review workflows.

Access and manage secrets stored in 1Password vaults. Retrieve credentials, SSH keys, API tokens, and secure notes directly in AI coding environments.

The Netlify MCP Server is Netlify's official Model Context Protocol integration (netlify/netlify-mcp), acting as a bridge between AI coding agents and the Netlify API/CLI so they can create, build, deploy, and manage Netlify projects using natural-language prompts instead of manual dashboard clicks or hand-written API calls. Installed via `npx -y @netlify/mcp` (requires Node.js 22+, and the Netlify CLI installed globally for the best experience), it connects to Windsurf, Cursor, Claude Desktop/Code, VS Code Copilot, Cline, Warp, LM Studio, and any other MCP-compatible client, with one-click install links published for several of them. Core capabilities include creating and managing sites, triggering and monitoring deploys, modifying access controls and team permissions, installing or uninstalling Netlify extensions, fetching user/team/site metadata, and creating or updating environment variables and secrets. Authentication runs through the Netlify CLI's existing login session, so agents inherit whatever account/team access the developer already has rather than requiring a separately scoped token. Typical use: ask Claude to "deploy the current branch as a preview and give me the URL" or "add a STRIPE_SECRET_KEY environment variable to the production site" and the agent executes the equivalent Netlify CLI/API calls directly, which is useful for developers who want deploy and config management folded into an AI pair-programming workflow instead of context-switching to the Netlify dashboard.

The Sentry MCP Server is Sentry's official Model Context Protocol integration, purpose-built for human-in-the-loop coding agents like Claude Code, Cursor, and Windsurf. Rather than exposing every Sentry API endpoint, it focuses tightly on developer debugging workflows: searching and triaging issues, pulling stack traces and event details, inspecting performance traces, and querying project/team/org metadata in natural language. The primary deployment is a hosted remote MCP server at mcp.sentry.dev, built on Cloudflare's remote-MCP infrastructure, so most users connect with zero local setup — just add the remote URL to their client. For self-hosted Sentry instances or local development, a stdio transport is also available via npx @sentry/mcp-server, authenticated with a Sentry User Auth Token scoped to org:read, project:read, project:write, team:read, team:write, and event:write. AI-powered search tools (search_events, search_issues) translate natural-language queries into Sentry's query syntax, but require a configured LLM provider (OpenAI, Azure OpenAI, Anthropic, or OpenRouter) — all other tools work without one. Claude Code users can also install it as a plugin (claude plugin install sentry-mcp@sentry-mcp) for automatic subagent delegation whenever a conversation touches Sentry errors, issues, or traces. This turns "why did this deploy break in production" into a direct conversational debugging session instead of tab-switching into the Sentry dashboard.

The Datadog MCP Server is Datadog's official Model Context Protocol integration that connects AI assistants directly to your Datadog observability platform — metrics, logs, APM traces, infrastructure, and monitors. Built and maintained by Datadog, the server uses your API and application keys to expose tools for querying live time-series metrics with full DQL expressions, searching log events with Datadog Log Management query syntax, retrieving distributed APM traces and service performance summaries, listing infrastructure hosts and their tags, and checking the status of Datadog monitors and downtime windows. This gives Claude real-time visibility into your production systems: ask "What's the p99 latency for the payments service over the last hour?" or "Find all ERROR-level logs from the auth service since the last deploy," and receive answers backed by live Datadog data rather than stale dashboards. Authentication requires a Datadog API key (DD_API_KEY) and an Application key (DD_APP_KEY) with appropriate scope — both available from Organization Settings > API Keys and Application Keys in the Datadog UI. Set DD_SITE to your Datadog region (e.g., datadoghq.com, datadoghq.eu, or us3.datadoghq.com). Works with Claude Desktop, Cursor, Windsurf, and any MCP-compatible client. Especially powerful for SRE, DevOps, and on-call workflows where engineers need AI to correlate metrics, logs, and traces during incident response without context-switching away from their conversation.

The official Grafana MCP server connects Claude and other AI assistants directly to your Grafana instance and its surrounding observability ecosystem, turning natural-language questions into dashboard lookups, incident investigations, and datasource queries. Dashboard tools cover search, retrieval, JSONPath-scoped property extraction, patch-based editing, and per-panel query/datasource introspection, with context-window-aware helpers like get_dashboard_summary so an agent never has to pull a full multi-megabyte dashboard JSON just to answer a simple question. Query tools speak PromQL against Prometheus (including histogram-percentile helpers), LogQL against Loki, and native query languages for InfluxDB, ClickHouse, CloudWatch, Graphite, Athena, Snowflake, Elasticsearch/OpenSearch, and Quickwit datasources — most gated behind opt-in --enabled-tools flags to keep the default tool surface lean. It also wraps Grafana Incident for creating and updating incidents, Sift for automated error-pattern and slow-request investigations, full alerting CRUD (rules, contact points, notification policies) across Grafana-managed and external Alertmanager sources, Grafana OnCall schedule/shift/alert-group management, RBAC-gated admin tools for teams/users/roles, deeplink generation so the LLM never has to guess a dashboard URL, annotations, snapshots, PNG rendering via the Grafana Image Renderer, and provisioning-repo validation for git-sync workflows. Ships as a Go binary or via uvx, authenticates with a Grafana service account token (Editor role or granular RBAC scopes), and every tool category can be individually disabled to control context-window usage.

Query and analyze your Axiom logs, traces, and all other event data in natural language.

Enable AI Agents to fix build failures from CircleCI.

Exposing Buildkite data (pipelines, builds, jobs, tests) to AI tooling.

Official Jenkins MCP Server plugin enabling AI assistants to manage builds, check job statuses, and retrieve logs.

The Terraform MCP Server is HashiCorp's official integration that brings Terraform's infrastructure-as-code capabilities into AI assistants via the Model Context Protocol. It connects Claude Desktop, Cursor, VS Code, and other MCP clients to the Terraform ecosystem — letting you explore providers, look up module schemas, validate configurations, and work with HCP Terraform (Terraform Cloud) all through natural-language conversation. Core tools include: search the Terraform Registry for modules and providers by keyword, retrieve full provider schema documentation including resource arguments and attribute types, look up specific module input/output variables and their defaults, resolve provider version constraints and compatibility matrices, and run Terraform operations against HCP Terraform workspaces including plan, apply, and state inspection. A key use case is AI-assisted IaC authoring: ask Claude to "generate a Terraform module for an AWS VPC with public and private subnets using the latest aws provider schema" and the server fetches the live provider schema to ensure accurate attribute names and types rather than hallucinating outdated syntax. For HCP Terraform users, workspace integration supports listing workspaces, triggering runs, and checking plan output. HashiCorp maintains the server at hashicorp/terraform-mcp-server and distributes it as a pre-built binary for Linux, macOS (arm64 + amd64), and Windows. Install via: `npx @hashicorp/terraform-mcp-server`. Pairs well with GitHub MCP for full IaC PR review workflows.

Deploy code to Google Cloud Run and interact with GCP services.

Interact with the Heroku Platform through LLM-driven tools for managing apps, add-ons, dynos, and databases.

The n8n MCP Server exposes your n8n workflow automation platform as a set of MCP tools, letting AI assistants trigger workflows, pass data to automations, and retrieve execution results — all through natural conversation. n8n is a self-hostable (and cloud-hosted) workflow automation tool with 500+ built-in integrations spanning CRMs, databases, email, Slack, GitHub, and more. The official n8n-mcp server (n8n-io/n8n-mcp) runs alongside your n8n instance and authenticates via your n8n API key. Available operations include: list all workflows in your instance, execute a specific workflow by name with custom input data, retrieve execution history and logs, and create or update workflow definitions. A typical use case: Claude triggers an n8n workflow that sends a Slack notification, creates a Jira ticket, and logs the event to a Google Sheet — all in a single natural-language request. n8n also supports acting as an MCP host itself, so you can configure AI tools within n8n workflow nodes. For cloud users, n8n's remote MCP endpoint is available at your n8n.cloud instance. Install locally with: `npx n8n-mcp` and set `N8N_API_URL` and `N8N_API_KEY` in your environment. Works with Claude Desktop, Cursor, VS Code, and all MCP-compatible clients.

PagerDuty MCP Server is PagerDuty's official, actively maintained local MCP server (github.com/PagerDuty/pagerduty-mcp-server) for managing incident response directly from an MCP-enabled client like Claude, Cursor, or VS Code. Beyond the standard tool surface for incidents, services, on-call schedules, and event orchestrations, it ships embedded React 'MCP Apps' that render interactive UIs inside supporting IDEs: an Incident Command Center with a real-time incident feed, timeline/notes/alert inspection, one-click acknowledge/escalate/resolve, and AI-powered similar-incident detection; an On-Call Manager for schedule overrides and escalation-policy edits; an On-Call Compensation Report tracking hours worked, interruption rates, and EU Working Time Directive compliance with CSV export; a Service Dependency Graph visualizing upstream/downstream impact; and an Onboarding Wizard for first-time account setup. The server runs as a single Python process via `uv run pagerduty-mcp`, avoiding a separate HTTP server to manage. Authentication uses a PagerDuty User API Token generated from My Profile → User Settings → API Access (Freemium accounts have role-based limits on who can generate one), used subject to PagerDuty's Developer Agreement. This combination of deep incident-lifecycle tooling and embedded operational dashboards makes it one of the more feature-complete official vendor MCP servers for on-call/DevOps teams.

The OpsGenie MCP Server bridges MCP-capable clients like Claude Desktop and Cursor to OpsGenie's alerting and on-call platform, so an on-call engineer can triage incidents from an AI assistant instead of switching to the OpsGenie web console. Alert tools cover list_alerts (with OpsGenie's powerful filter-query syntax for scoping by status, priority, tag, or team), get_alert for full detail, and acknowledge_alert/unacknowledge_alert for actually working an incident from chat. Team tools (list_teams, get_team) let an agent resolve who owns a given alert, and heartbeat tools (list_heartbeats, get_heartbeat) expose the health of OpsGenie's dead-man's-switch monitors — useful for an agent answering "is our nightly batch heartbeat still healthy?" without a dashboard. The server is written in Go, ships as a single binary installable via `go install`, and supports stdio, SSE, and streamable-HTTP transports plus a built-in self-update command. Authentication uses an OpsGenie API token set via the OPSGENIE_TOKEN environment variable (or a custom var name via --token-env-var). Important context: this is a community project, not an Atlassian first-party release — no official Atlassian OpsGenie MCP server exists, and Atlassian has been folding OpsGenie's alerting/on-call features into Jira Service Management's roadmap, so teams already on JSM should also check the Jira MCP Server entry on this site. The repo itself is now archived (last updated 2026-05) but the built binary remains functional for existing OpsGenie accounts.

Observability and monitoring with New Relic.

Manage and interact with the Dynatrace Platform for real-time observability and monitoring.

Query and analyze data, alerts, dashboards, and cross-reference production behavior with codebase.

Lightstep was a distributed-tracing and observability platform built on OpenTelemetry, acquired by ServiceNow in 2021 and folded into the ServiceNow Cloud Observability product line; its GitHub org still hosts the legacy OpenTelemetry Launcher and tracer SDKs for Go, Java, Python, Node.js, and C++, but none of those repos are MCP servers. Neither ServiceNow nor the community has shipped an MCP server exposing Lightstep/Cloud Observability trace and metric data to AI assistants — repeated GitHub and web searches across review cycles turn up zero results for "lightstep mcp" or "servicenow observability mcp" with any real implementation. If you need AI-agent access to distributed tracing data today, check this directory's Honeycomb or Grafana entries, which do have real, actively maintained MCP servers covering similar observability workflows. This entry is kept as a placeholder so the "lightstep mcp" search term stays discoverable and will be updated the moment ServiceNow or a community project ships a real server.

Feature flags as a service for continuous delivery.

Split.io was acquired by Harness and rebranded to Harness FME (Feature Management & Experimentation) — a `splitio/mcp-server` repo does not exist, and Harness has not published a first-party MCP server for it. The best available option is kud/mcp-harness-fme, a community-built, MIT-licensed TypeScript server exposing 30 tools across workspaces, environments, feature flags, flag definitions, segments, rule-based segments, and change requests. It supports a zero-config startup that reads the `MCP_HARNESS_FME_API_KEY` environment variable and exits immediately if it is missing, plus a "kill & restore" flow that instantly forces all traffic to a flag's default treatment (or restores it) with a single tool call. Every destructive operation — delete, kill, archive, disable — requires an explicit `confirm: true` argument, preventing accidental changes from an agent acting on ambiguous instructions. It also supports the full change-request flow for rule-based segments, letting teams submit segment-definition changes with optional approvers for orgs that require approval gates. Install with `npx --yes @kud/mcp-harness-fme@latest`, or add it directly via `claude mcp add --transport stdio --scope user harness-fme --env MCP_HARNESS_FME_API_KEY=your_api_key -- npx --yes @kud/mcp-harness-fme@latest` in Claude Code. An optional `get_flag_url` deep-link tool activates when `MCP_HARNESS_FME_ACCOUNT_ID` and `MCP_HARNESS_FME_ORG_GUID` are also set. Works with any stdio MCP client — Claude Desktop, Claude Code, Cursor, Windsurf, Cline, Zed.

The Flagsmith MCP Server is Flagsmith's official, Speakeasy-generated Model Context Protocol server for its Core and SDK APIs, letting AI assistants read and manage feature flags, remote config values, and environment/identity segmentation directly from a conversation. It ships as an installable Desktop Extension (`mcp-server.mcpb`) for Claude Desktop — drag-and-drop install with no additional setup — and as an npm package (`flagsmith`) for CLI-based clients, started with `npx flagsmith start --token-auth <your-api-token>` and wired into Claude Code, Cursor, Gemini, and Windsurf via each client's standard MCP config or one-line `mcp add` command. Progressive discovery keeps the tool surface manageable across the full Flagsmith API rather than dumping every endpoint into context at once. Typical use: ask Claude to "list all feature flags enabled for the beta segment in production" or "toggle the new-checkout-flow flag off for the EU environment," with the assistant calling the live Flagsmith API instead of requiring a dashboard visit. NOTE: as of this writing the repo carries an explicit "not yet ready for production use" notice from its Speakeasy-generated setup flow — expect rough edges and check the repo before depending on it for anything mission-critical.

Provides access to OpenTelemetry traces and metrics through Logfire.

Deploy your project to the cloud seamlessly with the Defang platform.

Analyze your reliability posture, review recent tests and chaos engineering experiments.

Chat with your builds, CI, and more.

Enable AI access to your CloudBees CI cluster, the Enterprise-grade Jenkins-based solution.

MCP server for DeployHQ API integration, enabling AI to manage deployments.

MCP Server for the JFrog Platform API, enabling repository management and build tracking.

Discovery, exploration, reporting and root cause analysis using all observability data.

Bring real-time production context—logs, metrics, and traces—into your local environment.

Query and interact with kubernetes environments monitored by Metoro.

Access network of thousands of probes to run ping, traceroute, mtr, http and DNS resolve.

Allows Homebrew users to run Homebrew commands locally.

CLI for interacting with GitKraken APIs, includes MCP server for Jira, GitHub, GitLab.

Official MCP server for Cortex.

Experimental MCP server for real-time compliance intelligence into your AI workflows.

Access Datadog metrics, logs, and traces from AI tools. Query infrastructure data, investigate incidents, and analyze performance using natural language.

Manage PagerDuty incidents, on-call schedules, and escalation policies from AI tools. Acknowledge, resolve, and query incidents through natural language.

Time-series database MCP for InfluxDB. Write and query metrics using Flux or InfluxQL. Ideal for monitoring, IoT, and observability data.

High-performance build system for JavaScript monorepos. Query task graphs, run builds, manage caching, and optimize pipelines with AI.

Smart build system for monorepos. Run tasks, understand project graph, generate code, and optimize CI pipelines across frameworks with AI assistance.

Build automation MCP for Java/Kotlin/Android projects. Run tasks, manage dependencies, analyze build scripts, and inspect Gradle project structure.

Java build and dependency management MCP server. Manage POM files, run lifecycle phases, resolve dependencies, and analyze Maven project structure.

Google's build system MCP server. Navigate Bazel build graphs, run targets, manage deps, and analyze large monorepo builds across languages.

Deploy and manage applications on Fly.io. Scale machines, inspect logs, manage secrets, and orchestrate global deployments via AI.

Railway's official MCP server puts your Railway projects — services, databases, environment variables, deployments, networking, volumes, and templates — inside natural-language reach of Claude Code, Cursor, GitHub Copilot, OpenAI Codex, Factory Droid, and OpenCode. As of the current release, the standalone `@railway/mcp-server` npm package is deprecated in favor of shipping MCP support directly inside the Railway CLI: running `railway mcp` starts a local stdio server, while `railway mcp install` auto-detects installed AI tools and writes the correct client config for you (add `--agent <tool>` to target one, or `--remote` to point clients at Railway's hosted server at mcp.railway.com instead of the local binary). The installer merges Railway's entry into existing MCP configs without clobbering other servers you've already set up. Once connected, you can ask your AI agent to spin up a new environment from a GitHub repo, roll environment variables across services, inspect deploy logs when a build fails, provision a Postgres or Redis instance, or manage networking and volume mounts — all without leaving your editor or touching the Railway dashboard. Because the CLI is the source of truth, keeping `railway` up to date is enough to pick up new MCP tools; there's no separate npm package to track anymore. The legacy `@railway/mcp-server` package still works as a compatibility shim — it detects a missing Railway CLI and prints migration instructions rather than failing silently.

Render's official MCP server connects AI coding tools directly to your Render cloud infrastructure — create and manage web services, static sites, background workers, cron jobs, and PostgreSQL/Redis databases without leaving your editor. The primary integration path is Render's hosted server at mcp.render.com/mcp, authenticated with a scoped Render API key generated from your Account Settings page; configure it in Cursor, Codex, Claude Code (via `claude mcp add --transport http`), Claude Desktop (via the `mcp-remote` bridge), or Jules with a few lines of JSON. Render also publishes the underlying implementation as an open-source Go project (render-oss/render-mcp-server) for teams that want to inspect or self-host the tool-calling logic. Core tools span workspace selection (list_workspaces, select_workspace), service management (list_services, get_service, create_web_service, create_static_site, create_cron_job with full runtime/plan/region options), deploy triggers, log and metrics inspection for debugging failed builds, and direct Postgres database queries from inside the LLM. Render explicitly flags that the server currently supports one potentially destructive action — modifying an existing service's environment variables — so it scopes API keys broadly but keeps write operations narrow. Typical prompts include "deploy this repo as a new Node web service in Oregon" or "show me the last 100 log lines for my API service and tell me why it's crashing." Because it's a hosted remote server, there's no local runtime to keep updated, and Render ships new tools directly through mcp.render.com without requiring a client-side package upgrade.

Invoke and manage AWS Lambda functions. Test functions locally, deploy code, view execution logs, and manage layers and event source mappings.

Manage EC2 instances, security groups, AMIs, and VPCs. Start/stop instances, query metadata, analyze costs, and automate infrastructure tasks.

Manage Linode/Akamai Cloud instances, object storage, and Kubernetes clusters. Deploy, resize, and monitor cloud resources via natural language.

Manage Hetzner Cloud servers, load balancers, and volumes. Deploy European cloud infrastructure, manage firewalls, and monitor resource usage via AI.

Manage Fastly CDN services, VCL configurations, and edge logic. Purge cache, deploy edge functions, and monitor real-time performance metrics.

Manage GitHub Actions workflows, runs, and secrets. Trigger workflows, inspect run logs, manage environment variables, and debug CI failures via AI.

Declarative GitOps continuous delivery for Kubernetes. Manage applications, sync deployments, inspect health status, and rollback releases via AI.

Kubernetes package manager MCP server. Install, upgrade, and roll back Helm charts. Inspect release history, manage repositories, and debug chart templates.

Query Prometheus metrics using PromQL from AI assistants. Analyze time-series data, set up alerting rules, and monitor infrastructure performance.

Manage secrets and sensitive data stored in HashiCorp Vault. Read and write secrets, manage dynamic credentials, and handle PKI operations via AI.

Service mesh and configuration management MCP. Query service discovery, manage KV store, inspect health checks, and configure intentions.

IT automation MCP server for Ansible. Run playbooks, manage inventories, inspect task results, and troubleshoot automation failures via AI.

Kubernetes-native CI/CD pipeline MCP. Manage Tekton tasks, pipelines, and runs. Inspect logs, trigger pipelines, and debug task failures with AI.

Comprehensive vulnerability scanner MCP. Scan container images, filesystems, and git repos for CVEs, misconfigurations, and secrets with Aqua's Trivy.

Runtime security detection MCP for Falco. Monitor container and host activity, detect anomalous behavior, query security events, and investigate incidents.

Transform data in your warehouse with dbt. Run models, test assertions, generate docs, inspect lineage, and manage dbt Cloud jobs via MCP.

Collect and query distributed traces, metrics, and logs using OpenTelemetry standards. Analyze application performance and correlate signals across services.

Open-source distributed tracing MCP for Jaeger. Query traces, inspect service dependencies, analyze latency distributions, and investigate production incidents.

High-performance time-series database MCP for VictoriaMetrics. Query metrics with MetricsQL, manage clusters, and analyze long-term storage efficiently.

Application performance monitoring MCP for Elastic APM. Query transaction traces, error rates, and service maps. Integrate with Kibana dashboards.

Load testing and performance engineering MCP for k6. Run performance tests, analyze results, configure VUs and scenarios, and integrate with Grafana Cloud.

Log aggregation MCP for Grafana Loki. Query log streams with LogQL, inspect labels, analyze error patterns, and correlate logs with metrics and traces.

Durable execution platform MCP for Temporal. Start and query workflows, signal and cancel executions, inspect workflow history, and manage worker processes.

Distributed task queue MCP for Celery. Monitor task execution, inspect queues, revoke and retry tasks, and analyze worker performance and failure patterns.

Modern workflow orchestration MCP for Prefect. Trigger and monitor flows, manage deployments, inspect run logs, and orchestrate data pipelines at scale.

Network discovery and security scanning MCP using Nmap. Scan ports, detect services, identify OS fingerprints, and analyze network topology for security research.

Parse, validate, and generate cron expressions via MCP. Get human-readable descriptions, next execution times, and validate scheduling syntax.

Execute commands on remote servers via SSH through MCP. Run shell commands, transfer files with SCP, manage SSH keys, and automate remote operations.

Manage multi-container Docker applications with Compose MCP. Start, stop, and scale services, inspect container logs, and manage service dependencies.

Advanced Kubernetes cluster management MCP. Manage namespaces, deployments, services, ingresses, and custom resources beyond what the basic kubectl server offers.

Execute AWS CLI commands via MCP. Query any AWS service, manage resources across regions, configure profiles, and automate complex multi-service workflows.

Execute gcloud commands via MCP. Manage GCP resources across all services, configure projects and IAM, and automate Google Cloud workflows.

Execute az commands via MCP. Manage Azure resources, subscriptions, and services. Automate infrastructure deployments and resource group management.

Manage Proxmox Virtual Environment hypervisor via MCP. Create and control VMs and LXC containers, manage storage, configure networking, and monitor cluster nodes.

Manage your Tailscale mesh VPN network via MCP. List devices, manage ACLs, view network status, and control peer connections across your tailnet.

Deploy and manage Cloudflare Pages projects via MCP. Trigger deployments, manage environment variables, configure custom domains, and inspect build logs.

Control AVM FRITZ!Box routers from your AI assistant. Manage connected devices, WiFi settings, network configurations, parental controls, and schedule timed actions.

Manage Render deployments from your AI assistant. Trigger deploys, check service status, manage environment variables, inspect build and deploy logs, and configure scaling settings.

Self-hosted Heroku/Netlify alternative control via MCP. Manage applications, databases, and services on your own infrastructure. Deploy from Git, manage environment variables, and monitor logs.

Apache Kafka MCP server for streaming data integration. Produce and consume messages, manage topics, inspect consumer groups, and build event-driven AI workflows with Kafka as your data backbone.

RabbitMQ MCP server for message queue management. Publish messages, consume from queues, inspect bindings, and monitor queue health. Perfect for integrating AI reasoning into event-driven microservice architectures.

Gradle build system MCP server for JVM and Android projects. Run tasks, inspect dependencies, check build variants, manage Android SDK configurations, and debug build failures through your AI assistant.

Atlassian Statuspage API server for querying component status, incident history, and maintenance windows. Monitor service status pages and create incident updates programmatically.

Balena fleet management MCP server for Linux IoT devices. Deploy containerized applications, manage device fleets, monitor resource usage, update configurations, and access device logs via balenaCloud API.

HashiCorp Vault secrets management MCP server. Read and write dynamic secrets, manage policies and tokens, rotate database credentials, retrieve PKI certificates, and query audit logs via Vault HTTP API.

HashiCorp Nomad workload orchestrator MCP server. Deploy and manage containerized and non-containerized applications, inspect job allocations, scale task groups, query node health, and manage namespaces via Nomad API.

Website and API uptime monitoring via UptimeRobot. Check monitor statuses, query downtime history, create new monitors, manage maintenance windows, and receive alert contact configurations.

API and browser monitoring as code via Checkly. Run API checks and browser tests, inspect check results and error logs, manage alert channels, trigger manual check runs, and view SLA metrics.

Incident management and log aggregation via Better Stack. Query structured logs, manage on-call schedules, view incident timelines, check monitor uptime, and manage status page incidents in real time.

Full-stack observability via Coralogix. Search logs with DataPrime query language, create alerts, inspect traces, analyze metrics, and investigate incidents across distributed applications and infrastructure.

Log management and security analytics via Sumo Logic. Run log queries with Sumo Logic Query Language, view dashboards, manage scheduled searches, and detect anomalies across cloud-native infrastructure.

Enterprise integration and API management via MuleSoft Anypoint Platform. Query APIs, manage integration flows, monitor runtime performance, and trigger Mule application deployments via CloudHub.

Dell Boomi iPaaS integration via MCP. Execute integration processes, query audit logs, manage connection settings, monitor real-time process results, and inspect deployed components on Boomi AtomSphere.

Interact with n8n workflow automation. Execute workflows, create new automations, manage webhook triggers, and inspect execution logs — all through natural language.

Trigger and manage Pipedream event-driven workflows. Run serverless functions, inspect workflow logs, manage HTTP triggers, and connect 900+ APIs with AI assistance.

Manage Benthos (Redpanda Connect) stream processing pipelines. Create, modify, and monitor data pipelines that process, transform, and route messages between systems.

Manage Vector data pipelines for log and metrics processing. Configure sources, transforms, and sinks; monitor pipeline health; and route observability data at scale.

Configure and monitor Telegraf metrics agent. Manage input/output plugins, inspect collected metrics, and orchestrate data collection from servers, containers, and IoT devices.

Manage Logstash data ingestion pipelines. Configure input/filter/output stages, monitor pipeline health, inspect queued events, and troubleshoot log processing issues.

Manage Kestra data orchestration workflows. Trigger flows, monitor executions, manage namespaces, and inspect task outputs in this open-source workflow automation platform.

Integrate with Tenable's vulnerability management platform (Nessus, Tenable.io). Query scan results, asset vulnerabilities, risk scores, and remediation guidance across your infrastructure.

Manage Oracle Cloud Infrastructure (OCI) resources including compute instances, storage, networking, databases, and Kubernetes clusters via the OCI SDK.

Manage Vultr cloud infrastructure including compute instances, bare metal servers, Kubernetes, block storage, and managed databases via the Vultr API.

Automate infrastructure configuration and management via SaltStack (Salt). Execute remote commands, manage state files, orchestrate deployments, and query minion data.

Manage infrastructure as code with Puppet. Query node reports, apply manifests, inspect resource states, manage Hiera data, and orchestrate Puppet agent runs across your infrastructure.

Control Node-RED flow-based programming for IoT and automation. Create and deploy flows, trigger injections, read node outputs, manage credentials, and integrate with hundreds of Node-RED nodes via MCP.

Monitor website uptime with Freshping. Query check statuses, retrieve incident history, manage alert contacts, and get performance metrics across your monitored URLs and APIs.

Query Sematext Cloud for log management and infrastructure monitoring. Search log data, inspect metrics, manage alert rules, and correlate logs with APM traces across your monitored services.

Query Graylog log management and SIEM platform via MCP. Search log streams using GELF queries, fetch alert conditions, access dashboards, correlate security events, and investigate incidents across distributed infrastructure.

Integrate with Chef infrastructure automation via MCP. Query node inventories, cookbooks, recipes, roles, environments, and data bags. Trigger Chef runs, audit compliance with InSpec, and manage infrastructure as code across cloud and on-premises environments.

Connect to Pulumi infrastructure as code via MCP. Query stacks, resources, updates, and drift detection. Preview and deploy cloud infrastructure changes across AWS, Azure, GCP, and 100+ cloud providers using your preferred programming language through Pulumi AI.

Connect to Cisco AppDynamics application performance management platform via MCP. Query business transaction health dashboards, tier dependency maps, error snapshot call chains, JVM heap diagnostic reports, and database query plan analyses. Access Cognition Engine anomaly detection events, policy violation alerts, agent installation health checks, and cloud-native Kubernetes cluster correlation data.

Integrate with IBM Instana automated application observability platform via MCP. Access service dependency graphs, infrastructure maps, website real-user monitoring traces, and SLI/SLO compliance summaries. Query unbounded analytics incident event correlations, pipeline acceleration CI/CD integration metrics, and Instana Sensor autodiscovery inventory updates for cloud-native and mainframe environments.

ClearML MLOps platform MCP — manage experiment tracking, model deployment, data versioning, and ML pipelines. Query task history, compare runs, clone experiments, and orchestrate distributed training jobs.

NATS messaging system MCP — publish and subscribe to subjects, manage JetStream streams and consumers, inspect cluster health, query message history, and interact with key-value stores and object stores.

Vitess MySQL-compatible distributed database clustering MCP — run queries on Vitess clusters, inspect shard topology, manage keyspaces, query VTAdmin API, and operate MySQL at scale with horizontal sharding and connection pooling.

ManageEngine IT management suite MCP — query incidents and service requests, manage assets in IT inventory, run reports, access network monitoring data, and interact with ServiceDesk Plus, OpManager, and ADManager modules.

Nx monorepo build system MCP — query project graph, run targeted builds and tests, manage dependencies between apps and libs, inspect affected projects, and leverage Nx caching and distributed task execution.

Turborepo monorepo task runner MCP — query pipeline configurations, run tasks with caching, inspect workspace dependencies, manage remote cache settings, and speed up builds across your JavaScript and TypeScript monorepo.

Backstage internal developer portal MCP — search the software catalog, retrieve service ownership and metadata, query TechDocs documentation, list registered APIs and components, check scaffolded templates, and explore your engineering ecosystem.

OpsLevel service catalog MCP — query service maturity scores, retrieve ownership and dependency graphs, check service level checks and rubrics, list teams and their services, and access infrastructure context for AI-powered DevOps workflows.

Incident.io incident management MCP — create and update incidents, query timeline events, list on-call schedules, retrieve postmortem drafts, manage follow-up actions, and access severity classifications for AI-assisted incident response.

Squadcast on-call and incident management MCP — query on-call schedules, create and acknowledge incidents, manage escalation policies, retrieve service health status, list past incidents, and trigger runbooks for automated incident response.

Bunny.net CDN and edge platform MCP — manage pull zones and storage buckets, purge CDN cache, query bandwidth and traffic analytics, configure edge rules, manage video stream libraries, and monitor CDN performance across global PoPs.

SigNoz open-source APM and observability MCP — query distributed traces and spans, retrieve service performance metrics, search structured logs, analyze error rates and latencies, manage alert rules, and monitor infrastructure health with OpenTelemetry data.

Icinga infrastructure monitoring MCP — query host and service check results, retrieve downtime and acknowledgement states, list monitoring objects and their health status, access performance data and trend graphs, and trigger manual checks on managed infrastructure.

Zabbix network and infrastructure monitoring MCP — query host and item data, retrieve active alerts and trigger states, search historical metrics, manage maintenance windows, access problem event timelines, and retrieve SLA reports for monitored systems.

Great Expectations data validation MCP — run expectation suites against data assets, retrieve validation results and data docs, manage checkpoints, query expectation store configurations, and surface data quality failures across your pipeline for AI-assisted debugging.

DVC (Data Version Control) ML pipeline MCP — query experiment runs and metrics, retrieve tracked dataset versions, compare model performance across commits, manage pipeline stages, access artifact storage locations, and reproduce ML experiments with version-controlled data.

Data orchestration and pipeline management via Dagster's API. Trigger asset materializations, monitor pipeline runs, query asset catalogs, manage partitions, and debug failures in your Dagster data platform.

Workflow orchestration and scheduling via Prefect's API. Trigger and monitor flow runs, inspect deployments, manage work pools, view logs, and automate data pipeline operations from your AI assistant.

Manage Apache Airflow DAGs and tasks via MCP. Trigger DAG runs, monitor task status, view logs, pause/unpause pipelines, and query execution metadata. Works with Airflow 2.x and Astro Cloud deployments.

IBM MQ queue manager integration via MCP. List local queue managers, run MQSC commands, inspect queue depths and channel status, and manage IBM MQ infrastructure. Built for enterprise messaging and event-driven architectures.

Cloudflare Workers development MCP server for on-the-fly application building with D1 databases, R2 object storage, KV stores, and other Workers bindings. Create tables, query data, upload objects, and manage Workers primitives directly from AI tools as you build Cloudflare applications.

BACnet protocol gateway for building automation and control networks. Query HVAC, lighting, and facility management devices via MCP.

CANopen industrial protocol MCP server for querying and controlling embedded field devices on CANopen networks in manufacturing and robotics.

EtherCAT real-time industrial Ethernet MCP integration. Read and write process data objects on EtherCAT slave devices for automation and motion control.

Inductive Automation Ignition SCADA/MES gateway MCP server. Browse OPC-UA tags, read historian data, and interact with Ignition projects via AI.

NetBox network source of truth MCP server. Query IP addresses, prefixes, devices, rack layouts, circuits, and DCIM data through the NetBox REST API.

Nautobot network automation platform MCP server. Interact with your network source of truth, jobs, and GraphQL API to automate network operations.

Cisco Meraki cloud-managed networking MCP server. Query network topology, clients, alerts, and device health across Meraki MX, MR, MS, and MV products.

Palo Alto Networks Panorama centralized firewall management MCP server. Query security policies, threat logs, and device status across your NGFW fleet.

Fortinet FortiGate next-generation firewall MCP server. Manage firewall policies, VPN tunnels, threat logs, and security profiles via FortiOS REST API.

Juniper Mist AI-driven networking MCP server. Query wireless clients, AP health, SLE metrics, and WAN insights through the Mist cloud API.

HPE Aruba Central network management MCP server. Monitor access points, switches, gateways, and clients across Aruba Central-managed networks.

Infoblox DDI (DNS, DHCP, IPAM) MCP server. Query and manage IP address space, DNS records, and DHCP leases through the Infoblox NIOS REST API.

Highlight.io open-source session replay and error monitoring MCP server. Query user sessions, errors, and logs to debug production frontend issues.

Baselime serverless and edge observability MCP server. Query distributed traces, logs, and metrics from AWS Lambda, Cloudflare Workers, and Vercel Edge Functions.

Interact with ArgoCD applications, sync statuses, rollback deployments, and manage GitOps pipelines.

Manage Flux CD GitOps resources, Kustomizations, HelmReleases, and sources for Kubernetes continuous delivery.

Provision and manage cloud infrastructure resources across providers using Crossplane compositions and XRDs.

Configure Istio traffic management, mTLS policies, service entries, and observability for Kubernetes services.

Manage KEDA ScaledObjects, ScaledJobs, and event-driven autoscaling triggers for Kubernetes workloads.

Manage Podman containers, pods, images, and volumes without requiring root privileges.

Manage Rancher multi-cluster Kubernetes environments, projects, namespaces, and workloads.

Manage Docker and Kubernetes environments through Portainer — stacks, containers, volumes, and networks.

Manage K3s lightweight Kubernetes clusters — deployments, services, ingress, and config on edge and IoT nodes.

Manage Perforce Helix Core version control — check out files, submit changelists, sync depots, manage users, and query revision history at enterprise scale.

Manage artifacts in Sonatype Nexus Repository — search Maven/npm/Docker components, check vulnerability data via OSS Index, and manage repository policies.

Stacked pull requests and code review for GitHub. Manage PR stacks, reviews, and merges programmatically.

Apache ActiveMQ integration for managing message queues, topics, and broker monitoring via MCP.

Amazon SQS server for sending, receiving, and managing messages in AWS Simple Queue Service queues.

Microsoft Azure Service Bus integration for cloud messaging, queues, and pub/sub topics via MCP.

Inngest serverless event-driven functions and background jobs — trigger, monitor, and manage workflows via MCP.

Trigger.dev background jobs and long-running tasks — create, monitor, and manage jobs from AI assistants.

Nagios monitoring server — query host/service status, acknowledge alerts, and manage downtime schedules.

LibreNMS network monitoring — discover devices, check port status, retrieve SNMP data, and manage alerts.

SNMP protocol server for querying network device metrics, interface statistics, and system information via MIBs.

Kong API Gateway management — configure routes, plugins, consumers, upstreams, and rate limits via MCP.

Security monitoring MCP that tracks the supply chain provenance of local MCP servers ensuring integrity and preventing tampering.

Official Harness CI/CD MCP server with 240+ tools for pipeline management, deployment automation, feature flags, and cloud cost optimization.

Manage OpsGenie alerts, on-call schedules, escalation policies, and incident response workflows.

Manage incidents, runbooks, and retrospectives through FireHydrant for faster, AI-assisted incident response.

Manage Azure ML experiments, datasets, compute clusters, model registries, and deployments through AI-assisted MLOps workflows.

Query VictoriaMetrics for fast, cost-effective time-series data storage and analytics — compatible with Prometheus and Graphite.

Integrate Codecov code coverage platform for test coverage reporting, coverage trend analysis, pull request comments, flagging, and team coverage metrics across repositories.

Use Grype open-source container and filesystem vulnerability scanner for SBOM-based vulnerability detection, CVE lookups, policy enforcement, and CI/CD security gates.

Generate Software Bill of Materials (SBOM) with Syft for containers, filesystems, and package managers — producing CycloneDX or SPDX format SBOMs for compliance and supply chain security.

Integrate Aqua Security cloud-native security platform for container scanning, Kubernetes runtime protection, serverless security, CI/CD pipeline security, and compliance automation.

Connect to Sysdig cloud security platform for runtime threat detection, vulnerability management, cloud security posture management (CSPM), and Kubernetes security monitoring.

Integrate Losant enterprise IoT platform for device management, real-time data collection, workflow automation, edge computing, and IoT application development.

Connect to ChirpStack open-source LoRaWAN Network Server for device provisioning, gateway management, uplink/downlink data, and geolocation for LPWAN IoT deployments.

Access Helium decentralized wireless network API for IoT device connectivity, coverage maps, hotspot data, token rewards, and LoRaWAN sensor data streams.

Access Coveralls test coverage service for coverage history tracking, pull request comments, badge generation, and team coverage trend analysis across multiple languages.

Integrate Trunk code quality meta-linter for running multiple linters, formatters, and security scanners with unified configuration, caching, and CI/CD integration.

Connect to Depot remote Docker build service for 40x faster Docker builds with shared caching, native ARM support, and drop-in compatibility with existing CI/CD pipelines.

Integrate Earthly reproducible build tool for containerized builds with Makefile-like syntax, local and CI caching, monorepo support, and language-agnostic build definitions.

Connect to Tilt smart rebuilds for Kubernetes development workflows — automatic live updates, dependency graphs, health monitoring, and team dev environment standardization.

Implement OpenADR 2.0 automated demand response for energy management — VTN/VEN server integration, DR event handling, price signals, and grid flexibility programs.

Manage Apache Kafka clusters — topic management, consumer groups, message production/consumption, schema registry, Kafka Connect connectors, and cluster health monitoring.

Query Prometheus time-series metrics, execute PromQL, explore metric labels, manage alerting rules, check alert states, and visualize metric trends for SRE workflows.

Manage Grafana dashboards, panels, data sources, alerting, annotations, and on-call schedules — query dashboards programmatically and create alerts from natural language.

Access HashiCorp Vault for secrets management — read/write secrets, dynamic credentials, PKI certificates, SSH key signing, encryption as a service, and audit log queries.

Automate Octopus Deploy release management — create and promote releases, trigger deployments across environments, manage runbooks, query deployment history, and monitor tenanted multi-environment pipelines via REST API.

Interact with Atlantis pull request automation for Terraform — trigger plan and apply runs, list pending workflow locks, check workspace status, view atlantis.yaml config, and manage project-level access policies.

Work with CDK for Terraform (CDKTF) stacks — synthesize HCL from TypeScript/Python/Java constructs, plan and apply stacks against cloud providers, query state outputs, and manage CDKTF project scaffolding via CLI.

Monitor and triage Bugsnag error reports — query error trends and affected users, update error states and assignments, link errors to deploys, set stability scores, and correlate crashes with release versions.

Integrate with Rollbar error monitoring — query occurrences and stack traces, update item statuses, manage deploy tracking, set notification rules, retrieve person-level error context, and generate stability reports.

Manage LaunchDarkly feature flags programmatically — create and toggle flags, define targeting rules and percentage rollouts, query evaluation reasons, manage environments and projects, and retrieve flag change audit logs.

Centralized firewall management via Palo Alto Panorama API — query security policy rules and NAT policies, retrieve threat logs and traffic analytics, manage address objects and service groups, push configuration changes across device groups, retrieve device health and resource utilization, manage security profiles, and audit configuration diffs and compliance posture.

Firewall policy management via Check Point Management API — query and create security rules and access control policies, manage network objects and host definitions, retrieve threat prevention logs and IPS signatures, publish and install policy changes, monitor gateway health, retrieve VPN tunnel status, and audit security policy compliance.

Network security management via SonicWall NSM API — query firewall rules and access policies, retrieve VPN tunnel status and user sessions, monitor threat events and IPS signatures, manage address objects and service groups, retrieve bandwidth utilization and interface statistics, configure content filtering rules, and manage SonicWall device fleet from a centralized dashboard.

Infrastructure monitoring via PRTG API — retrieve sensor status and alert conditions, query bandwidth utilization and traffic graphs for network interfaces, manage device groups and monitoring trees, acknowledge alerts and set maintenance windows, retrieve historical performance data, manage notification triggers, and monitor uptime and response time for hosts and services.

Backup and recovery management via Veeam REST API — query backup job status and schedule, trigger on-demand backup and restore operations, retrieve restore points and recovery metadata, monitor infrastructure health and backup repository capacity, manage replication jobs and failover plans, retrieve audit logs and compliance reports, and monitor SLA adherence across protected workloads.

Data protection and cybersecurity via Acronis Cyber Cloud API — manage backup plans and policies, retrieve backup status and restore points for endpoints and workloads, initiate recovery operations, monitor antimalware scan results and threat detections, retrieve patch management status and vulnerability assessments, manage tenant hierarchies, and track storage consumption and quota usage.

Enterprise data management via Commvault Command Center API — manage backup and restore jobs, query protection status for virtual machines, databases, and cloud workloads, retrieve SLA compliance reports, initiate granular recoveries and disaster recovery tests, manage storage policies and data aging, access audit trails, and monitor infrastructure health across hybrid environments.

Disaster recovery and continuous data protection via Zerto API — monitor Virtual Protection Groups and replication health, retrieve RPO metrics and recovery point history, initiate failover and failback operations, manage recovery sites and VM protection, access journal-based recovery checkpoints, retrieve compliance and analytics reports, and monitor WAN bandwidth consumption for replication traffic.

Scalable build system integration via Bazel — query build targets and dependency graphs, run incremental builds and tests with caching, retrieve build event protocol data, analyze build performance and bottlenecks, manage remote execution and caching configuration, query workspace rules and macro definitions, and integrate with CI/CD systems for hermetic, reproducible builds.

Privileged access management via CyberArk REST API — retrieve and rotate credentials from the Digital Vault, manage safe permissions and member assignments, query privileged session recordings and audit logs, manage account onboarding and platform policies, retrieve just-in-time access requests, monitor dual control approvals, access threat analytics and risk scores, and integrate with SIEM and ticketing systems.

Privileged identity and remote access management via BeyondTrust API — manage privileged credentials and rotation schedules, retrieve session recordings and keystroke logs, manage remote support sessions and endpoints, query least privilege policy violations, access password vault contents with policy enforcement, manage role-based access and approval workflows, and integrate with ticketing systems for session authorization.

Manage secrets and encryption via HashiCorp Vault — read and write secrets from KV secret engines, generate dynamic database and cloud credentials, manage PKI certificates, access AppRole and Kubernetes auth methods, rotate static secrets, query audit logs, manage policies and tokens, and integrate secrets management into CI/CD pipelines and infrastructure automation.

Access 1Password secrets and vaults via the 1Password CLI and Connect API — retrieve secrets by reference path, query vault items, manage secrets in CI/CD environments, inject environment variables from vault, list team vaults and permissions, rotate credentials, manage service account tokens, and integrate secrets retrieval into development and deployment workflows.

Interact with Apache Pulsar distributed messaging via the Pulsar admin API — manage topics, namespaces, and tenants, publish and consume messages, configure message retention and TTL, manage subscriptions and consumer groups, query topic statistics and backlog, handle schema registry, configure geo-replication, manage authentication and authorization, and monitor broker health.

Query observability data via the New Relic NRQL API — run NRQL queries across APM metrics, distributed traces, and logs, access application performance baselines, query error rates and response times, manage alert policies and conditions, pull infrastructure metrics for hosts and containers, access synthetic monitor results, and build dashboards and SLO compliance reports.

Access Elastic APM observability via the Elasticsearch and Kibana APIs — query service performance metrics, distributed traces, and error rates, analyze transaction latency percentiles, pull infrastructure and host metrics, access ML anomaly detection results, manage APM agent configuration, query log correlation data, build service maps, and monitor real user monitoring (RUM) analytics.

Search and analyze application logs via the Loggly API — query log events with Lucene syntax, filter by source and severity, pull log volume trends, set up and manage alerts on log patterns, access parsed fields and custom tags, analyze error frequency across services, pull field distribution statistics, and integrate log search into incident investigation workflows.

Access Papertrail cloud log management via the Papertrail API — search log archives with wildcard and regex queries, tail live log streams, manage log routing to systems and groups, set up alert notifications, query events by source host and program, access historical log archives, pull usage statistics, and integrate log search into DevOps and SRE incident response workflows.

Search and manage logs via LogDNA/Mezmo — query log lines with field-based filtering, access streaming log tails, manage log views and saved queries, configure alert policies on patterns, pull log usage metrics, manage ingestion exclusion rules, access log parsing configurations, export log archives, and integrate centralized log analysis into observability and compliance workflows.

Manage infrastructure as code via Terraform CLI and the Terraform Cloud API — run plan, apply, and destroy operations, query state files and resource inventory, manage workspaces and variable sets, access run history and logs, handle module registry, manage Sentinel policies, query cost estimates, manage team permissions, and integrate IaC workflows into GitOps and CI/CD pipelines.

Deploy and manage Cloudflare Workers serverless functions via the Cloudflare API — deploy worker scripts, manage KV namespaces and bindings, query R2 storage buckets, handle Durable Objects, manage D1 databases, configure routing and triggers, access analytics for request volume and latency, manage secrets and environment variables, and handle Wrangler-based deployment workflows.

Manage Netlify deployments and JAMstack workflows via the Netlify API — deploy sites from Git, manage build hooks and deploy previews, configure environment variables and secrets, query deploy logs and build status, manage domain DNS and SSL certificates, configure edge functions, access form submissions, manage split testing, pull bandwidth and function invocation analytics, and trigger rollbacks.

Manage Vercel deployments and frontend infrastructure via the Vercel API — deploy projects from Git, manage environment variables across environments, query deployment logs and build output, configure custom domains and SSL, manage edge configs and edge middleware, access serverless function logs, pull project analytics, manage team members and access tokens, and handle preview deployment workflows.

Manage Heroku cloud applications via the Heroku Platform API — deploy apps via Git push, manage dynos and scaling, configure add-ons and environment variables, query application logs, manage Heroku Postgres databases, handle pipelines and review apps, manage team access, view billing and dyno usage, run one-off dynos for maintenance tasks, and trigger rollbacks to previous releases.

Manage secrets and environment configurations via the Doppler API — fetch secrets for any project, config, and environment; inject environment variables into local dev and CI/CD pipelines; sync secrets across staging, production, and review environments; manage access controls and service tokens; audit secret access logs; rotate API keys; and build automated secret management workflows.

Access Infisical open-source secrets management via their API — read and write secrets across projects and environments; manage secret folders, tags, and overrides; pull secrets for dynamic injection into apps and CI/CD; configure service tokens and machine identities; audit secret change history; sync with AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager; and manage team permissions.

Sync and manage .env files across teams via Dotenv Vault — push and pull encrypted .env files to the vault, manage environment-specific configs for development, staging, and production, share secrets with teammates securely, generate .env.vault encrypted backup files, integrate with CI/CD pipelines for automatic secret injection, and audit who accessed which environment variables.

Automate GitHub issue resolution via Sweep AI's coder bot API — create Sweep tasks from issue descriptions, retrieve PR status and code change summaries, access Sweep's codebase understanding and search results, manage sweep.yaml configuration files, pull task completion metrics, access refactoring and test generation workflows, and integrate Sweep into CI/CD pipelines for automated code maintenance and technical debt reduction.

Query and analyze log aggregation data from Grafana Loki via the LogQL API — execute LogQL log stream and metric queries, retrieve log lines with label filtering and regex matching, pull log volume metrics and rate calculations, access label discovery and value enumeration, manage log retention policies and storage tiers, build log-based alerting rules, and integrate Loki log data with Grafana dashboards and incident response workflows.

Access distributed tracing data from Grafana Tempo via TraceQL — query traces by service, operation, duration, and attribute values using TraceQL syntax, retrieve full span trees and trace timelines, analyze latency distributions and error rates across services, correlate traces with Loki logs and Prometheus metrics, access service graph data and RED metrics, pull trace exemplars, and build distributed system debugging and performance analysis workflows.

Manage and query OpenTelemetry Collector pipelines via the zPages and pprof extension APIs — retrieve pipeline status for receivers, processors, and exporters; access trace and metric sampling statistics; manage collector configuration hot-reloading; pull internal telemetry and performance metrics; manage batch processor queues; access log pipeline throughput data; and build OTel Collector administration and observability automation workflows.

Control Vector observability data pipeline via its GraphQL API and REST endpoints — retrieve pipeline topology and component status, query throughput and error rate metrics for sources, transforms, and sinks, access internal telemetry and buffer health, hot-reload pipeline configurations, manage Vector Remap Language (VRL) transform logic, pull component-level performance profiling, and build data pipeline administration and monitoring automation.

Privileged access security platform (formerly Thycotic/Centrify). Manage privileged credentials, enforce least privilege, and audit all privileged activity.

Manage Terraform Cloud workspaces, runs, state, and variables. Trigger plans, view logs, and approve applies via HCP Terraform API.

Interact with Apache NiFi data flow pipelines via the NiFi REST API — query and manage process groups, processors, and connections, start and stop flow components, retrieve provenance data, monitor queue depths and data lineage, manage controller services, deploy flow templates, and build AI-assisted data pipeline monitoring and orchestration workflows.

Orchestrate and monitor Apache Beam data processing pipelines via the Beam API — submit pipeline jobs to Dataflow, Spark, or Flink runners, retrieve job status and metrics, access pipeline graphs, query transformation outputs, manage job state and cancellations, and integrate Beam pipeline management into AI-driven data engineering workflows.

Monitor applications via Uptrace OpenTelemetry backend — query distributed traces and spans, retrieve service performance metrics, access log data, view error rates and P99 latencies, analyze trace attributes and custom metrics, monitor deployment health, and integrate OpenTelemetry observability into AI-assisted incident investigation and performance optimization workflows.

Monitor and manage Linkerd service mesh via the Linkerd CLI and Viz API — retrieve service topology and traffic maps, query per-route success rates and latency histograms, access TLS certificate status, retrieve pod-level proxy metrics, monitor multi-cluster links, debug traffic with Linkerd tap, and integrate service mesh observability into AI-driven platform engineering workflows.

Interact with Envoy Proxy admin interface and xDS management — retrieve cluster and endpoint health, query route configuration and listener stats, access circuit breaker and retry stats, retrieve active connections and request counters, read configuration dumps, manage dynamic xDS configurations, and integrate Envoy-based service proxy management into AI-driven traffic engineering workflows.

Manage Vagrant development environments via the Vagrant CLI — create and provision virtual machines from Vagrantfiles, start, stop, and destroy VMs, retrieve VM status and SSH connection info, run provisioning scripts, manage snapshots, list box inventories, and automate local development environment lifecycle with AI-assisted environment orchestration.

Manage GitHub Dependabot security alerts and updates via the GitHub REST API — list and triage dependency vulnerabilities, retrieve CVSS scores and affected packages, dismiss or escalate security alerts, access auto-merge pull request statuses, query version update configurations, bulk-update Dependabot PRs, and integrate automated dependency security management into AI-driven DevSecOps workflows.

Extend GitLab project management and CI/CD via the GitLab REST and GraphQL APIs — manage issues, epics, and milestones beyond the base GitLab MCP, access advanced merge request workflows, retrieve runner status and CI pipeline details, query deployment environments and audit events, manage labels and boards, access time tracking data, and build enterprise GitLab automation workflows.