rtfmbro-mcp

rtfmbro-mcp

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

https://github.com/user-attachments/assets/dbe0b3b4-a42c-4e91-8bcd-a94d430ef0b8

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• Stale Documentation: AI models often rely on outdated training data about packages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

Agent Integration

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

• GitHub Copilot: Copy .github/copilot-instructions.md to your project
• Claude Code: Copy CLAUDE.md to your project root
• Cursor: Copy .cursor/rules to your project root
• Other agents: Adapt the instructions from either file above to your agent’s format

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

• Rust (crates.io)
• Go (pkg.go.dev)
• Java/Kotlin (Maven Central)
• C#/.NET (NuGet)
• Ruby (RubyGems)

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.