by mcp-get
LLM.txt Directory — Quickly access up-to-date API documentation and developer resources for modern LLM integrations.
Searches and retrieves content from LLM.txt files, which contain structured documentation and API information for AI applications.
LLM.txt Directory is a community-built MCP server published by mcp-get that provides AI assistants with tools and capabilities via the Model Context Protocol. LLM.txt Directory — Quickly access up-to-date API documentation and developer resources for modern LLM integrations. It is categorized under ai ml, developer tools.
You can install LLM.txt Directory in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
LLM.txt Directory is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend LLM.txt Directory for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, LLM.txt Directory benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
LLM.txt Directory has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: LLM.txt Directory surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated LLM.txt Directory against two servers with overlapping tools; this profile had the clearer scope statement.
LLM.txt Directory is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Strong directory entry: LLM.txt Directory surfaces stars and publisher context so we could sanity-check maintenance before adopting.
LLM.txt Directory is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
LLM.txt Directory is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Strong directory entry: LLM.txt Directory surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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This repository contains a collection of community-maintained Model Context Protocol (MCP) servers. All servers are automatically listed on the MCP Get registry and can be viewed and installed via CLI:
npx @michaellatman/mcp-get@latest list
Note: While we review all servers in this repository, they are maintained by their respective creators who are responsible for their functionality and maintenance.
You can install any server using the MCP Get CLI:
npx @michaellatman/mcp-get@latest install <server-name>
For example:
npx @michaellatman/mcp-get@latest install @mcp-get-community/server-curl
To run in development mode with automatic recompilation:
npm install
npm run watch
We welcome contributions! Please feel free to submit a Pull Request.
While this repository's structure and documentation are licensed under the MIT License, individual servers may have their own licenses. Please check each server's documentation in the src directory for its specific license terms.
If you find these servers useful, please consider starring the repository!
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.