MCP Servers

Official MCP server for GitHub repo operations

GitHub MCP Server is the official Model Context Protocol server from GitHub that connects AI assistants to repositories, issues, pull requests, workflows, and code search. It exposes 100+ operations with toolset filtering, permission scoping, and audit logging, available in both remote-hosted and self-hosted Docker deployment modes.

Official open catalog of Model Context Protocol servers

The official, community-run registry for discovering and publishing Model Context Protocol (MCP) servers — an open index that MCP clients read to find available servers.

Up-to-date docs for AI code editors via MCP

Context7 is an MCP server developed by Upstash that injects up-to-date, version-specific documentation directly into AI code editors and coding assistants. By typing 'use context7' in prompts, developers get accurate library documentation instead of hallucinated or outdated API references. It pulls from official source documentation and serves it through the Model Context Protocol, solving the common problem of LLMs generating code with incorrect or nonexistent API calls.

Official Chrome DevTools MCP server for coding agents

chrome-devtools-mcp is the Chrome DevTools team's official MCP server that lets coding agents control and inspect a live Chrome browser with first-party Chrome DevTools Protocol fidelity. It exposes Network inspection, Performance traces, Lighthouse audits, console output, and structured DOM snapshots as typed MCP tools, so agents can debug real pages and ship reliable web performance investigations without resorting to brittle DOM scraping.

Open-source Docker gateway for containerized MCP server orchestration

Docker MCP Gateway is Docker's open-source orchestration layer for Model Context Protocol servers. It gives MCP clients one gateway, launches catalog servers in isolated containers on demand, injects credentials, applies runtime restrictions, and routes tool requests. Catalogs and profiles let teams reuse approved server collections across clients, while Docker Desktop can run the gateway automatically with MCP Toolkit enabled.

Apache-2.0 Python framework for building MCP servers, clients, apps, and deployable agent tool surfaces.

FastMCP is an Apache-2.0 Python framework for building MCP servers, clients, and apps with decorators, type hints, transports, auth patterns, deployment docs, and telemetry hooks. The project now resolves to PrefectHQ/fastmcp, with Prefect Horizon available as a separate enterprise MCP gateway for identity, RBAC, audit, monitoring, and server governance.

Memory engine and context API for AI assistants

Supermemory is a memory and context platform for AI assistants and agents. It ranks #1 on LongMemEval, LoCoMo, and ConvoMem, supports MCP for Claude/Cursor-style clients, provides plugins for developer tools, and combines memory extraction, user profiles, hybrid search, connectors, and RAG in one API.

LSP-powered semantic coding agent via MCP

Serena is a free, open-source coding agent toolkit that provides IDE-like semantic code retrieval and editing capabilities to any LLM via the Model Context Protocol (MCP). Built on Language Server Protocol (LSP) integration, it enables symbol-level navigation, cross-file refactoring, and relational code understanding across Python, TypeScript, Go, Rust, Java, PHP, and more — without requiring file-level reads or text-based search.

Open data platform wrapping any SQL database with instant APIs

Directus is a database-first open data platform that wraps any existing SQL database with instant REST and GraphQL APIs, a no-code admin dashboard, and built-in authentication. Unlike traditional headless CMS platforms that impose their own data model, Directus introspects your existing schema and works on top of it — supporting PostgreSQL, MySQL, SQLite, MS SQL, MariaDB, and CockroachDB out of the box.

Graph RAG code knowledge graph for repository exploration

GitNexus is a code-knowledge-graph and Graph RAG app for exploring repository structure before humans or AI coding agents make changes. Write-time source checks support graph/RAG and local-server signals, but not hard local/server-architecture, 14-language, MCP, pricing, or licensing claims; evaluate privacy, scale, and integrations directly.

Official authenticated remote MCP endpoint for Linear issues, projects, comments, and coding-agent workflows.

Linear MCP Server is Linear’s official authenticated remote MCP endpoint for agent access to issues, projects, and comments. It gives Claude, Codex, Cursor, VS Code, Windsurf, Zed, and other clients a centrally hosted way to find, create, and update Linear work items through OAuth-backed MCP without maintaining a local connector or brittle API glue.

Official Python SDK for building MCP servers

The official Python SDK for the Model Context Protocol, enabling developers to build MCP servers and clients with asyncio support. Provides type-safe tool definitions, resource management, and all standard MCP transports. The most popular Python package for MCP development with comprehensive documentation.

AI-driven task management for agentic coding

Taskmaster AI is an open-source task management system for AI-driven development that turns PRDs into structured, dependency-aware coding tasks. It runs as an MCP server inside Cursor, Claude Code, Windsurf, Lovable, and Roo, giving AI agents a disciplined workflow instead of ad-hoc code generation. Supports multiple AI providers with configurable main, research, and fallback models.

Codebase knowledge graph MCP server for AI coding agents

Codebase Memory MCP is an MIT-licensed MCP server that turns a repository into a persistent code knowledge graph for AI coding agents. It gives Claude Code, Cursor, Codex-style agents, and other MCP clients structural queries for functions, classes, call chains, routes, and architecture, helping them explore large projects without repeatedly rereading files or relying only on broad search.

Real-time web search and retrieval via MCP

Exa MCP Server provides AI coding agents with real-time web search and content crawling capabilities through the Model Context Protocol. It leverages Exa's neural search API for semantic understanding of queries, returning clean, structured results with full page content extraction. Supports both remote hosted MCP endpoints and local client configurations.

MCP server that gives coding agents structured Figma context for design-to-code work

Figma Context MCP is an MCP server for giving coding agents structured access to Figma design context during implementation. Instead of copying screenshots or hand-written design specs into prompts, teams can expose layout, component, and context information to agents such as Cursor, Claude Code, and other MCP-compatible coding workflows. It is a strong design-to-code bridge for teams trying to reduce hallucinated UI details and tighten handoff between designers and AI-assisted developers.

Web scraping and crawling via MCP for AI agents

Firecrawl MCP Server is the official MCP integration for Firecrawl, giving Cursor, Claude, Windsurf, and other MCP clients scrape, crawl, map, search, extract, and agent-style web research tools. It now supports a hosted remote endpoint, keyless rate-limited scrape/search/interact use, API-key/OAuth access for the full tool set, and self-hosted Firecrawl deployments.

Go implementation of the Model Context Protocol SDK

mcp-go is a Go implementation of the Model Context Protocol, providing both server and client SDKs for building MCP integrations in Go. It supports stdio and SSE transports, resource management, tool registration, and prompt templates. Designed for Go developers building MCP servers for DevOps tools, CLI applications, and backend services. Over 8,000 GitHub stars.

Cloud browser automation via MCP for scalable testing

Browserbase MCP Server gives MCP clients a hosted or self-hostable browser through Browserbase and Stagehand. It exposes tools for starting sessions, navigating, acting, observing, extracting, and taking screenshots, with a hosted Streamable HTTP endpoint for easiest setup and local STDIO/Docker options for teams that want to run the Apache-licensed server themselves.

Context compression for LLM apps and coding agents

Headroom is an Apache-2.0 context compression layer for LLM apps and coding agents. It compresses tool output, logs, files, RAG chunks, and agent history through a local library, proxy, wrapper, or MCP server, with retrieval hooks for bringing originals back when needed. Treat its savings numbers as Headroom-reported benchmarks, not independent aicoolies measurements.

Tool infrastructure for AI agents

Composio connects AI agents to 1,000+ app toolkits with managed auth, delegated user connections, sessions, tool search, MCP gateway support, CLI workflows, and sandboxed workbench execution. It targets developers building Claude, Codex, Cursor, LangChain, CrewAI, OpenAI Agents SDK, and custom agent workflows that need authenticated business actions without hand-rolling every API integration.

Official remote MCP server for design-to-code and write-to-canvas Figma workflows.

Figma MCP Server is Figma’s official remote Model Context Protocol surface for design-to-code agents. It gives supported clients structured design context, variables, components, selected-frame code context, Code Connect mappings, and beta write-to-canvas tools for creating or updating native Figma frames from an MCP client while keeping the workflow tied to Figma files.

MCP server for controlling Windows desktops through UIAutomation

Windows-MCP is an open-source MCP server for giving AI agents structured access to Windows desktop automation. It focuses on UIAutomation, snapshots, input control, and Windows-specific app workflows, making it different from general filesystem or shell MCP servers.

Read/write MCP bridge between AI coding agents and Figma

Talk to Figma MCP is an MIT-licensed bridge from Grab that connects Cursor, Claude Code, and other MCP-capable agents to Figma through a local MCP server, WebSocket bridge, and Figma plugin. Unlike read-only context servers, it can inspect selections, create or modify nodes, update text in bulk, and automate design operations, so teams should review permissions before enabling write access.

Official Slack MCP server for approved workspace search, messaging, canvas, and user-context actions.

Slack MCP Server is Slack’s official remote MCP layer for giving approved AI clients workspace context and controlled actions. It lets agents search messages, files, users, and channels, draft or send messages, read threads, manage canvases, and authenticate through Slack OAuth while workspace admins approve integrations and normal Slack rate limits still apply.

MCP server registry and hosting

Registry and management platform for Model Context Protocol (MCP) servers that helps teams securely discover, install, deploy, and connect MCP servers for AI assistants. Smithery combines a searchable catalog, CLI setup, hosted deployments, namespaces, connection APIs, and scoped service-token flows for clients such as Claude, Cursor, Windsurf, and Codex.

Open-source RAG-based text-to-SQL engine

Vanna AI is an MIT-licensed text-to-SQL and SQL-agent framework with 23.6K+ GitHub stars. Its current Vanna 2.0 story adds user-aware agents, access control, audit logs, streaming UI components, and optional hosted admin features for teams that need natural-language database access without locking into one LLM or database. The original repo is now archived, so verify the current Vanna 2.0 path before adoption.

MCP server for connecting AI assistants to Supabase projects

Supabase MCP is Supabase's Apache-2.0 server for connecting AI assistants to Supabase projects. It can expose database, configuration, and project-management workflows to MCP clients such as Cursor, Claude, and Windsurf, while the official docs emphasize permission and security review before production use, SQL changes, or high-privilege database access.

MCP servers for AWS cloud services and workflows

AWS MCP Servers is a collection of open-source MCP server implementations from AWS Labs that connect AI coding agents to AWS services. It includes servers for AWS documentation, knowledge bases, and managed cloud workflows, enabling agents to provision resources, query docs, and manage infrastructure through the Model Context Protocol.

Email API service that gives AI agents their own inboxes and identities

AgentMail is a YC S25 startup that provides email infrastructure specifically designed for AI agents. It gives each agent its own email address and inbox, enabling agents to send, receive, and manage email conversations independently. With $6 million in seed funding from General Catalyst and Paul Graham, and over 500 B2B customers, AgentMail solves the identity and communication gap that arises when organizations deploy autonomous agents that need to interact via email.

Official SDK for building Claude-powered agentic applications

Anthropic's official SDK for building agents with Claude. Provides high-level abstractions for tool use, multi-turn conversations, computer use, and agent loops on top of the Claude API. Simplifies the development of production-grade agents by handling common patterns like retry logic, context management, and tool orchestration in a well-tested library.

Tool platform for AI agents

Arcade AI is an MCP runtime platform for secure agent authorization, reliable tool execution, and governance. It enables enterprises to deploy authenticated AI agents across Gmail, Slack, Salesforce, and 100+ other services without managing OAuth complexity or token refresh cycles. Arcade provides a centralized authorization layer that handles authentication, permission scoping, and compliance for every tool call an agent makes.

Official Asana remote MCP server for project and task workflows.

Asana MCP Server is Asana's official hosted MCP endpoint for connecting compatible AI clients to Asana work data. It lets authenticated users search workspace objects, inspect and manage tasks or projects, create work items, and generate project summaries through OAuth-backed Streamable HTTP access while preserving existing Asana permissions and admin app-management controls.

Official remote MCP server for Jira and Confluence

Atlassian's official remote MCP server connects Jira and Confluence to LLM clients, IDEs, and agent platforms over OAuth, so Claude, Cursor, and other MCP-aware tools can search issues, read pages, and post updates inside the same permission boundaries users already have. As a vendor-hosted reference implementation, it standardizes the Atlassian side of remote Model Context Protocol deployments.

Connect Blender to AI through Model Context Protocol

BlenderMCP bridges Blender and AI assistants like Claude through the Model Context Protocol, enabling natural language control over 3D modeling workflows. Artists and developers can create, modify, and manipulate 3D scenes, objects, materials, and animations by describing what they want instead of navigating complex menus. The tool exposes Blender's Python API through MCP, supporting operations from mesh creation to shader editing and physics simulations.

Automate local Chrome browser via MCP

BrowserMCP is an MCP server that enables AI agents to automate a local Chrome browser — navigating pages, clicking elements, filling forms, extracting content, and taking screenshots. It gives coding agents the ability to interact with web applications the way a human would, directly from Claude Desktop, Cursor, or any MCP client.

MCP integration for Cloudflare Workers and edge services

Cloudflare MCP Server connects AI coding agents to Cloudflare's edge platform through the Model Context Protocol. It enables agents to manage Workers, KV stores, R2 storage, D1 databases, and other Cloudflare services directly from AI assistants, streamlining edge application development and deployment workflows.

Swiss-army MCP server for local system automation

DesktopCommanderMCP is a general-purpose MCP server that gives AI agents the ability to execute local programs, read and write files, search the filesystem, and edit text files. It acts as a comprehensive local system actuator, enabling coding agents to interact with the development environment beyond just code editing.

MCP gateway and integration catalog for AI agents

Executor is an MIT-licensed integration layer and MCP gateway for AI agents. It gives Claude Code, Cursor, Codex, and other MCP-speaking clients one endpoint for connected OpenAPI specs, GraphQL APIs, MCP servers, Google Discovery sources, and custom JavaScript tools, with local, cloud, and self-hosted deployment options for teams centralizing tool access.

Zero-config conversion of FastAPI endpoints into MCP tools

FastAPI-MCP automatically converts existing FastAPI endpoints into Model Context Protocol tools with zero configuration. With 11,700+ GitHub stars, it is the most popular MCP integration layer, enabling thousands of FastAPI developers to make their APIs accessible to AI agents like Cursor and Claude through the MCP standard.

Turn a Figma design system into a programmable API for AI assistants

Figma Console MCP is open-source design-system infrastructure that exposes Figma to AI assistants through MCP. It supports structured extraction, design creation and editing, debugging, accessibility audits, and bidirectional design-token workflows across local, remote read-only, and paired cloud modes; it is not a generic one-click Figma-to-code exporter.

MCP server for AI-powered reverse engineering

GhidraMCP is an MCP server that enables LLMs to autonomously perform reverse engineering tasks through NSA's Ghidra disassembly framework. It exposes binary analysis capabilities like decompilation, function listing, cross-references, and symbol analysis as MCP tools, letting AI assistants generate malware reports and analyze compiled binaries.

Instant MCP server for any GitHub repository

GitMCP is a free, open-source remote MCP server that transforms any GitHub repository or GitHub Pages site into an AI-accessible documentation hub. Just replace github.com with gitmcp.io in any repo URL to give AI assistants grounded context about that project — eliminating code hallucinations with zero configuration required.

Pull Requests as a Service with AI + developers

GitStart is a YC-backed platform that delivers merge-ready pull requests by combining AI coding agents with human developer oversight. Teams assign sprint-sized tickets and the AI Ticket Studio converts vague requirements into well-scoped specs, then hybrid agents generate production-ready code through a five-stage quality process with a 98% merge rate reported across customer teams.

MCP server directory and gateway

AI gateway and model management platform that provides a unified API for accessing multiple LLM providers (OpenAI, Anthropic, Google, Mistral, and more) through a single endpoint. Features model routing, cost tracking, usage analytics, rate limiting, and API key management across providers. Simplifies multi-provider AI integration by handling authentication, billing, and failover in one place. Useful for teams evaluating multiple models or building provider-agnostic AI applications.

MCP server for secure database tooling with AI agents

Google GenAI Toolbox is an open-source MCP server from Google that specializes in easy, fast, and secure database tools for AI agents. It provides structured database access through the Model Context Protocol, enabling agents to query, inspect schemas, and manage data across supported databases with built-in security controls.

First-party MCP server for querying and managing Grafana

Grafana's official Model Context Protocol server, letting AI assistants search dashboards, query datasources, and manage alerts/incidents on your Grafana instance through a standard MCP interface.

Build real-time temporal knowledge graphs for AI agents

Graphiti is an open-source Python framework by Zep for building temporally-aware knowledge graphs for AI agents. It continuously integrates conversations, business data, and external information into queryable graphs with bi-temporal tracking. The hybrid retrieval combines semantic search, BM25 keywords, and graph traversal for sub-300ms queries without LLM calls at retrieval time.