GitHub stars as of 2026-10-03Descriptions and install commands are curated. Check each server's repository before installing.
What this tool does
Production-ready MCP servers are easiest to identify by maintainer and maintenance status. This directory tracks 39 Model Context Protocol servers across 6 categories with install commands and GitHub activity. Official reference servers from the Model Context Protocol project and vendor-owned servers such as Cloudflare, Stripe, and Supabase are the safest starting points; 8 early reference servers are now archived upstream and should not be used for new deployments.
Updated .
Provided as is. Check the output before you rely on it in production.
How to use MCP Server Directory
1
Browse by category
Filter servers by category: Official, Developer Tools, AI & LLM, Data & APIs, Productivity or Community.
2
Copy the install command
Expand a server to see its install command and copy it. Pin a version before you rely on a server in production.
3
Check the repository
Every entry links to its GitHub repository. Read the README there for required environment variables, API keys and runtime versions.
4
Search and sort
Search by name, description, author or tag, and sort the list to find what you need.
Questions and answers
What is MCP Server Directory?
MCP servers are small programs that give AI assistants such as Claude access to tools and data. This directory lists them by category with author, GitHub stars, transport type and a copyable install command, and can be searched by name, description, author or tag and sorted by stars, name or date added.
What is the Model Context Protocol (MCP)?
MCP is an open protocol that lets AI assistants connect to external tools and data through servers that expose capabilities such as file access, database queries or API calls. This directory lists MCP servers with install commands and links to their source repositories.
For AI agents: how to call this tool
Machine-readable contract, endpoints and examples. Humans can ignore this section.
Best Path For Builders
Browser workflow
Runs instantly in the browser with private local processing and copy/export-ready output.
Browser Workflow
This tool is optimized for instant in-browser execution with local data handling.
Run it here and copy/export the output directly.
/mcp-directory/
For automation planning, fetch the canonical contract at /api/tool/mcp-directory.json.
Which MCP servers are production ready?
There is no official certification for MCP servers, so "production ready" comes down to verifiable signals: who maintains the server, whether it is actively maintained or archived, how widely it is deployed, and whether its permission scope fits your threat model. The table below lists the 31 actively maintained servers in this directory, sorted by GitHub stars. Star counts refresh weekly; data as of 2026-09-27.
Actively maintained MCP servers (31)
Server
Maintainer
Category
Transport
GitHub Stars
Filesystem
Model Context Protocol
Official
stdio
91.0k
Memory
Model Context Protocol
Official
stdio
91.0k
Fetch
Model Context Protocol
Official
stdio
91.0k
Sequential Thinking
Model Context Protocol
Official
stdio
91.0k
Git
Model Context Protocol
Developer Tools
stdio
91.0k
Everything
Model Context Protocol
Community
stdio
91.0k
Context7
Upstash
AI & LLM
stdio
62.6k
Chrome DevTools
ChromeDevTools
Developer Tools
stdio
52.9k
Playwright
Microsoft
Data & APIs
stdio
37.8k
GitHub
GitHub
Official
stdio
33.3k
Serena
Oraios AI
Community
stdio
30.0k
FastMCP
Prefect
AI & LLM
stdio
28.0k
n8n Workflows
Romuald Członkowski
Data & APIs
stdio
23.0k
Figma Context
Graham Lipsman
AI & LLM
stdio
15.9k
Firecrawl
Firecrawl
Data & APIs
stdio
7.5k
Exa Search
Exa Labs
Community
stdio
5.1k
Notion
Notion
Productivity
stdio
4.7k
Obsidian
Markus Pfundstein
Productivity
stdio
4.5k
Cloudflare
Cloudflare
Data & APIs
stdio
4.3k
Supabase
Supabase
Data & APIs
stdio
2.9k
MySQL
Ben Borla
Community
stdio
2.1k
Stripe
Stripe
Data & APIs
stdio
1.9k
Kubernetes
Suyog Sonwalkar
Developer Tools
stdio
1.6k
Google Calendar
Nathan Spady
Productivity
stdio
1.2k
Sentry
Sentry
Developer Tools
stdio
906
Docker
Christian Kreiling
Developer Tools
stdio
746
Todoist
Abhiram Nair
Productivity
stdio
393
Linear
Jeremy Hadfield
Developer Tools
stdio
347
AWS MCP Servers
AWS Samples
Community
stdio
244
LangChain Tools
Andrew Wason
AI & LLM
stdio
205
Raygun
Raygun
Community
stdio
22
Reference servers maintained by the Model Context Protocol project share the star count of the modelcontextprotocol/servers monorepo. Source: each server's GitHub repository, refreshed 2026-09-27.
How do I evaluate an MCP server before production use?
Check the maintainer. Servers owned by the vendor of the underlying service (GitHub, Cloudflare, Stripe, Supabase, Microsoft's Playwright) track API changes fastest.
Check maintenance status. Several early reference servers are archived and no longer receive fixes — archived servers are listed below and should be treated as end-of-life.
Review the permission scope. A filesystem or database server should be configured with the narrowest possible access (allowed directories, read-only credentials) before an agent can call it.
Prefer stdio transport for local, single-user setups and audit any server that makes outbound network calls with your data.
Pin versions. Install commands like npx -y fetch the latest release; pin an exact version in production so server behavior does not change under your agent.
Which MCP servers are archived?
These 8 servers are archived upstream. They may still work today, but they no longer receive security fixes or API updates, so do not build new production deployments on them:
PostgreSQL, SQLite, Brave Search, Google Maps, Slack, Puppeteer, EverArt, Google Drive.