MCP server
by marckrenn
Rtfmbro is an MCP server for config management tools—get real-time, version-specific docs from GitHub for Python, Node.j
Fetches exact version-specific documentation for packages directly from GitHub repositories. Ensures AI assistants and developers get accurate, up-to-date docs that match the exact package versions being used.
Rtfmbro is an official MCP server published by marckrenn that provides AI assistants with tools and capabilities via the Model Context Protocol. Rtfmbro is an MCP server for config management tools—get real-time, version-specific docs from GitHub for Python, Node.j It is categorized under developer tools. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.
You can install Rtfmbro 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 supports remote connections over HTTP, so no local installation is required.
MIT
Rtfmbro 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
Rtfmbro reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
According to our notes, Rtfmbro benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Rtfmbro has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired Rtfmbro into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Rtfmbro benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Rtfmbro for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We wired Rtfmbro into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Rtfmbro is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Rtfmbro has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Rtfmbro surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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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.
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.
| Ecosystem | Registry | Status |
|---|---|---|
| Python | PyPI | ✅ Full Support |
| Node.js | npm | ✅ Full Support |
| Swift | SPM | 🚧 Alpha |
| GitHub | Direct | ⚠️ Fallback |
node_modules etc. lacks high-level documentation, browsing it is usually token-consuming and inefficientrtfmbro tries to solve these issues by:
.md, .mdx, .txt, .rst, .html) from the repositoryThe 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 |
claude mcp add-json rtfmbro '{ "type": "http", "url": "https://rtfmbro.smolosoft.dev/mcp/" }'
Add the remote server to your MCP configuration:
{
"rtfmbro": {
"type": "http",
"url": "https://rtfmbro.smolosoft.dev/mcp/"
}
}
To truly integrate rtfmbro with your AI coding agent of choice, copy the appropriate meta-instruction file to your project:
.github/copilot-instructions.md to your projectCLAUDE.md to your project root.cursor/rules to your project root| 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. |
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.