Convex MCP Server Pricing 2026

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 MongoDB MCP server is the official Model Context Protocol integration from MongoDB, giving AI assistants conversational access to both MongoDB Community Server and MongoDB Atlas cloud databases. With this MCP server, developers can ask Claude, Cursor, or Windsurf to query collections with natural-language filters that translate to MongoDB query syntax, run aggregation pipelines for analytics, insert and update documents, inspect collection schemas and index definitions, list databases and collections, and even manage Atlas clusters — all without leaving the AI interface. Common workflows include debugging slow queries by asking the AI to explain query plans, generating sample data for development environments, building dynamic dashboards by asking Claude to aggregate and summarize collection data, and automating routine maintenance like dropping orphaned indexes or counting documents matching conditions. The server works with MongoDB Atlas (via Atlas connection string) and self-hosted MongoDB 4.4+ instances. Authentication uses a standard MongoDB URI. Install with: `npx mongodb-mcp-server`. Compatible with Claude Desktop, Cursor, VS Code, Windsurf, and all MCP-compliant clients. With official backing from the MongoDB team and strong community adoption, this is the definitive MCP server for MongoDB AI integration.

The PostgreSQL MCP server is an official Model Context Protocol server maintained by Anthropic that gives AI assistants read-only access to PostgreSQL databases. By connecting Claude Desktop, Cursor, or VS Code to a running Postgres instance, developers can ask natural-language questions about their data schema, run exploratory SQL queries, inspect table structures, list available schemas, and analyze query results — all without leaving their AI chat interface. The server operates in read-only mode by design, preventing any accidental data mutations, making it safe to connect against production databases for reporting, debugging, and data exploration workflows. Core tools include executing SELECT queries, listing tables and schemas, describing column types and constraints, and inspecting indexes. Setup requires a running PostgreSQL instance and a standard connection string in postgres:// format. Install via npx using the @modelcontextprotocol/server-postgres package, passing your database URI as an argument. Teams use it to power data analysis conversations, generate schema documentation automatically, debug production data anomalies by asking Claude to inspect table contents, and build ad-hoc reports through natural-language SQL generation. Works with any PostgreSQL 12+ instance including Amazon RDS, Supabase, Neon, and self-hosted deployments.

The SQLite MCP server is an official Anthropic reference implementation that gives AI assistants direct, conversational access to SQLite databases — the world's most widely deployed database engine. Through natural language, you can ask Claude or Cursor to run SELECT queries, insert and update rows, inspect table schemas, create new tables, and generate business intelligence reports without writing a single SQL statement manually. Common use cases include exploring local data files, prototyping application schemas, auditing CSV imports, running ad-hoc analytics on app databases, and letting AI agents manage lightweight structured storage during agentic workflows. The server exposes tools for query execution, schema introspection, and memo-style business insights that synthesize query results into readable summaries. It requires a path to an existing .db file as a startup argument. Install with: npx @modelcontextprotocol/server-sqlite /path/to/your-database.db. Works with Claude Desktop, Cursor, VS Code, and all MCP-compatible clients. For developers who want AI to reason directly over structured data stored locally, the SQLite MCP server is the fastest path from question to answer without leaving your AI chat interface.

The Redis MCP server is an official Anthropic reference implementation that lets AI assistants interact with Redis key-value stores for caching, session management, pub/sub messaging, and real-time data operations. Redis is the most popular in-memory data store, widely used for rate limiting, leaderboards, job queues, and ephemeral session state — and this MCP server brings all of that within reach of natural-language AI prompts. With it, you can ask Claude or Cursor to get and set string/hash/list/set/sorted-set values, inspect TTLs, flush specific keys, publish messages to channels, and scan keyspaces for debugging — all without opening redis-cli. Developers use it during backend debugging sessions, to inspect live cache state, to manage feature flags stored in Redis, and to wire AI agents into event-driven architectures via pub/sub. The server connects to a Redis instance via a connection URL (defaults to redis://localhost:6379). Install with: npx @modelcontextprotocol/server-redis. Works with Claude Desktop, Cursor, VS Code, and any MCP-compatible client. It is the reference implementation for Redis + AI integration in the MCP ecosystem.