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ai-mldeveloper-tools

LLM.txt Directory

by mcp-get

LLM.txt Directory — Quickly access up-to-date API documentation and developer resources for modern LLM integrations.

Access up-to-date API documentation efficiently.

github stars

66

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Focuses on LLM.txt standard filesPart of community MCP server collection

best for

  • / AI developers needing current API documentation
  • / Building context-aware LLM applications
  • / Accessing structured documentation for AI tools

capabilities

  • / Search LLM.txt files by content
  • / List available LLM.txt documentation files
  • / Fetch complete content from LLM.txt files
  • / Perform contextual searches across documentation

what it does

Searches and retrieves content from LLM.txt files, which contain structured documentation and API information for AI applications.

about

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.

how to install

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.

license

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.

readme

MCP Get Community Servers

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.

Available Servers

  • LLM.txt Server - A server for searching and retrieving content from LLM.txt files. Provides tools for listing available files, fetching content, and performing contextual searches.
  • Curl Server - A server that allows LLMs to make HTTP requests to any URL using a curl-like interface. Supports all common HTTP methods, custom headers, request body, and configurable timeouts.
  • macOS Server - A server that provides macOS-specific system information and operations.

Installation

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

Development

To run in development mode with automatic recompilation:

npm install
npm run watch

Contributing

We welcome contributions! Please feel free to submit a Pull Request.

License

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.

Support

If you find these servers useful, please consider starring the repository!

FAQ

What is the LLM.txt Directory MCP server?
LLM.txt Directory is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for LLM.txt Directory?
This profile displays 26 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Discussion

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Ratings

4.626 reviews
  • Pratham Ware· Dec 24, 2024

    I recommend LLM.txt Directory for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Aanya Liu· Dec 4, 2024

    According to our notes, LLM.txt Directory benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Sophia Abbas· Nov 23, 2024

    LLM.txt Directory has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Yash Thakker· Nov 15, 2024

    Strong directory entry: LLM.txt Directory surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Sophia Li· Oct 14, 2024

    We evaluated LLM.txt Directory against two servers with overlapping tools; this profile had the clearer scope statement.

  • Dhruvi Jain· Oct 6, 2024

    LLM.txt Directory is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Ira Sethi· Sep 25, 2024

    Strong directory entry: LLM.txt Directory surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Sophia Thomas· Sep 21, 2024

    LLM.txt Directory is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Sofia Khan· Aug 16, 2024

    LLM.txt Directory is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Sophia Verma· Aug 12, 2024

    Strong directory entry: LLM.txt Directory surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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