Logfire MCP Server Pricing 2026

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.

Query your ClickHouse database server for analytics workloads.