Skip to main content
Glama
zero-abd

llmmcp

by zero-abd
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

llmmcp

MCP Registry

🌐 Website: https://llmmcp.vercel.app 🎥 Demo:

https://github.com/user-attachments/assets/eaad8d05-b7a8-4bf0-86c6-4fe2726da628

Stop LLM hallucinations and outdated code patterns.

llmmcp is a Model Context Protocol (MCP) server that provides real-time, up-to-date documentation for major LLM providers (OpenAI, Anthropic, and Google Gemini). It ensures your AI agents—like Cursor, Claude Desktop, or Windsurf—base their work on current official documentation instead of stale training data or deprecated library patterns.

Why use llmmcp?

LLMs frequently hallucinate about their own latest versions, feature availability (e.g., tool use in certain models), and pricing. llmmcp fixes this by providing:

  • ✅ Up-to-Date Model Info: Always know the latest available models (e.g., Gemini 2.0 Flash, Claude 3.5 Sonnet).

  • ✅ Detailed API Params: Verified tool use syntax, context window sizes, and rate limits.

  • ✅ Latest Implementation Patterns: Force your AI agent to follow current best practices instead of using legacy or deprecated library versions.

  • ✅ Real-Time Search: Queries an indexed vector database of official provider documentation.

  • ✅ Dynamic Listings: Get the current state of providers without hardcoded lists.

Related MCP server: Context7 MCP

🚀 Quick Start

You can use llmmcp immediately in your favorite AI tools without local installation.

Cursor

Add a new MCP server in Settings > Models > MCP Servers:

  • Name: llmmcp

  • Type: command

  • Command: npx -y llmmcp@latest

Claude Desktop

Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "llmmcp": {
      "command": "npx",
      "args": ["-y", "llmmcp@latest"]
    }
  }
}

🛠 Features

search_docs

Search the latest official documentation for specific technical details. Example: "What are the tool use parameters for Gemini 1.5 Pro?"

list_providers

Get a dynamically updated list of available providers (OpenAI, Anthropic, Google) and their currently promoted models.

🏗 How it Works

llmmcp is designed for speed and reliability:

  1. Indexer: A weekly scraper fetches raw markdown/text from official documentation.

  2. Vector DB: Chunks are embedded and stored in Pinecone with integrated embedding support.

  3. Backend: A Cloudflare Worker handles query embedding and retrieval, caching frequent results in Workers KV.

  4. MCP Client: A thin CLI translates MCP requests into API calls for the Worker.

🤝 Contributing & Self-Hosting

This project is open-source. If you'd like to run your own instance of the backend:

  1. See Architecture & Deployment (coming soon, see current setup in logs).

  2. Fork the repo and submit a PR for new documentation sources.

Developed by Abdullah Al Mahmud

License

MIT

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • Context7 MCP

    geobio
    A
    license
    Not graded
    quality
    D
    maintenance
    Provides LLMs with up-to-date, version-specific documentation and code examples from library sources directly into prompts, eliminating outdated code generation and hallucinated APIs.
    1,132,952 npm
    MIT

  • Context7 MCP

    3737123Dush
    A
    license
    A
    quality
    C
    maintenance
    Provides LLMs with up-to-date, version-specific documentation and code examples directly from library sources, eliminating outdated training data and hallucinated APIs by fetching current documentation at prompt time.
    2
    1,132,952 npm
    MIT