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rtfmbro-mcp

marckrenn/rtfmbro-mcp · 93 stars · MIT

MCP server rtfmbro provides always-up-to-date, version-specific package documentation as context for coding agents. An alternative to context7

Install

The repo has no one-line install. Follow its README.

Open the repo

Files

README.md

rtfmbro-mcp

rtfmbro provides always-up-to-date, version-specific package documentation as context for coding agents. An alternative to context7.

rtfmbro-mcp_720p.mov

Demonstration of rtfmbro in use, fetching a specific version (3.1.1) of Flask's readme and docs.

Overview

rtfmbro is a Model Context Protocol (MCP) server that provides real-time, version-aware documentation fetching for packages across multiple ecosystems. It bridges the gap between AI agents and accurate, up-to-date package documentation by fetching docs directly from GitHub repositories at the exact version your project uses.

Supported Ecosystems

Ecosystem Registry Status
Python PyPI ✅ Full Support
Node.js npm ✅ Full Support
Swift SPM 🚧 Alpha
GitHub Direct ⚠️ Fallback

Why rtfmbro?

The Problem

  • Stale Documentation: AI models often rely on outdated training data about packages
  • Missing Context: Source code in node_modules etc. lacks high-level documentation, browsing it is usually token-consuming and inefficient
  • Version Mismatches: Generic documentation doesn't match your specific package version, especially for legacy projects or brand new packages

The Solution

rtfmbro tries to solve these issues by:

  1. Version-Precise Fetching: Retrieves documentation from the exact git tag/commit that matches your lockfile
  2. Comprehensive Coverage: Extracts all documentation files (.md, .mdx, .txt, .rst, .html) from the repository
  3. Intelligent Caching: SHA-based currency checking ensures docs stay fresh without unnecessary re-fetching
  4. Agent Integration: Seamlessly integrates with AI coding assistants via the Model Context Protocol
  5. Great DX: Zero seting up for developers, just add the server to your MCP configuration, instructions and start fetching docs

MCP Tools

The server exposes four primary tools to AI agents:

Tool Purpose Parameters Returns
get_readme Fetches and returns the README file for a specific package version package, version, ecosystem README content as string
get_documentation_tree Generates a comprehensive folder structure of all documentation files package, version, ecosystem Tree structure as string
read_files Reads specific documentation files with optional line range slicing package, version, ecosystem, requests[] Dictionary mapping paths to content
search_github_repositories Searches for GitHub repositories using the GitHub Search API query, sort, order, per_page Formatted repository search results

Installation & Setup

Quick Start

Claude Code

claude mcp add-json rtfmbro '{ "type": "http",  "url": "https://rtfmbro.smolosoft.dev/mcp/" }'

Claude Desktop / VS Code / etc.

Add the remote server to your MCP configuration:

{
  "rtfmbro": {
    "type": "http", 
    "url": "https://rtfmbro.smolosoft.dev/mcp/"
  }
}

Cursor

Install MCP Server

Agent Integration

To truly integrate rtfmbro with your AI coding agent of choice, copy the appropriate meta-instruction file to your project:

How It Works

Documentation Workflow

  1. Registry Lookup: Queries the package registry (PyPI, npm, etc.) for metadata
  2. GitHub Discovery: Extracts the GitHub repository URL from package metadata
  3. Version Resolution: Fetches available git tags and matches them against your semantic version
  4. Smart Fetching: Clones the repository at the exact matched tag/commit
  5. Content Filtering: Extracts only documentation files, removing source code and build artifacts
  6. Caching & Currency: Stores results with SHA-based currency checking for efficient re-access

Caching Strategy

  • SHA-Based Validation: Compares current repository commit SHA with cached version
  • Automatic Invalidation: Re-fetches documentation when new commits are detected
  • Persistent Storage: Maintains local cache to avoid redundant GitHub API calls
  • Metadata Preservation: Stores documentation tree structure for fast browsing

Prerequisites

  • Package must be published to a supported registry (PyPI, npm)
  • Package metadata must contain a valid GitHub repository link
  • Repository must use git tags for version management
  • Documentation files must be present in the repository (not just generated sites)

Roadmap

Near Term

  • Ecosystem independent fallback: Implement a fallback mechanism for unsupported ecosystems
  • Provide rtfmbro source code: Open source the server codebase
  • Public docker image: Create a public Docker image for easy deployment
  • Private repo support: Allow authenticated access to private repositories
  • Add Tests: Implement unit and integration tests for core functionality
  • Enhanced Python Support: Include pydocs and docstring extraction
  • Search Capabilities: Search across documentation corpus

Future Ecosystems / Languages / Registries

Source code hosting and repository support:

  • GitHub: Support for GitHub repositories
  • Gitlab: Support for GitLab repositories
  • Bitbucket: Support for Bitbucket repositories
  • Launchpad: Support for Launchpad repositories

Known Issues

  • Some packages may have documentation in separate standalone repos
  • Large repositories may take a bit of time to clone and process initially

Similar / Additive Projects

  • mcp-package-docs: Another MCP server for package documentation, focusing on documentation extraction, LSP servers, etc. May be a great supplement to rtfmbro.
  • rust-docs-mcp-server: MCP server for Rust documentation, focused on Rust-specific features and documentation formats.
  • mcp-ragdocs: MCP server for RAG (Retrieval-Augmented Generation) documentation, aimed at improving the documentation experience for AI models.
  • godoc-mcp: MCP server for Go documentation, providing access to Go package documentation via the Model Context Protocol.
  • context7: Alternative to rtfmbro

Differences between context7 and rtfmbro

Aspect context7 rtfmbro
Actuality Scrapes documentation ahead-of-time at intransparent intervals or upon user trigger. As of writing, the "latest" Next.js docs are already 2 days old. Fetches documentation just-in-time, ensuring it's always up-to-date.
Version-specific docs Theoretically allows scraping older versions (useful for legacy or longtime projects), but the process is complicated, limiting practical availability effectively to latest versions. Fetches older documentation just-in-time, and always remains current, identical to latest docs.
Search strategy Uses either A) optionally token-limited RAG search to filter/preprocess docs which can be hit-or-miss, or B) dumps all content into LLM's context, resulting in excessive token-use. Employs agentic discovery (as used by Claude Code itself)
Developer Experience Requires explicitly mention of context7 in every prompt. Operates via defined rules/instructions, auto-selecting appropriate package name/version from lock file ("set and forget").
Support Language/ecosystem independent. Currently language/ecosystem-specific; planned additional languages/ecosystems and language-independent fallback mechanism soon.

Facts

Kind
MCP server
Repo
marckrenn/rtfmbro-mcp
Group
Uncategorized
Stars
93
License
MIT
Last push
2025-06-19
Forks
10
Topics
agent, agentic-ai, claude, docs, documentation, mcp, mcp-server, context7

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