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Autodocument MCP Server

MCP Server

AI‑powered auto documentation for code repositories

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Updated May 26, 2025

About

Autodocument automatically scans repository directories, generates comprehensive documentation, test plans, and senior‑level code reviews using OpenRouter’s Claude model. It respects .gitignore rules, updates existing files, and provides progress reporting for long runs.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Autodocument MCP Server Overview

Autodocument is an MCP (Model Context Protocol) server designed to automatically generate comprehensive documentation for code repositories. By leveraging the OpenRouter API, it analyzes directory structures and source files to produce Markdown artifacts such as , , and . The tool addresses a common pain point for developers: keeping documentation in sync with rapidly evolving codebases. Instead of manually writing or updating README files, Autodocument performs a bottom‑up traversal—starting from leaf directories and building up a coherent hierarchy—ensuring that every module, class, or function is covered in contextually relevant documentation.

The server’s core value lies in its AI‑powered generation. It uses Claude 3.7 (or any model specified via ) to produce natural‑language explanations, test plans with edge cases, and senior‑level code reviews focused on security and best practices. Developers can configure file extensions, size limits, and prompts to tailor the output for their specific language or project style. The integration with Git ( awareness) means that generated files ignore temporary or build artifacts, keeping the repository clean.

Key capabilities include:

  • Smart Directory Analysis: Recursively scans repositories, respecting rules.
  • Automatic File Creation: Generates documentation files at each directory level, updates existing ones, and falls back to summary files for large directories.
  • Progress Reporting: Emits detailed updates during long runs, preventing timeouts in AI assistants.
  • Extensible Architecture: Modular design allows future expansion (e.g., adding auto‑testing or code metrics tools).

In practice, Autodocument shines in scenarios such as onboarding new team members, preparing code for open‑source release, or maintaining legacy systems where documentation is sparse. A developer can trigger the tool via an MCP‑enabled assistant (Roo, Cline, or Claude Desktop), and receive a ready‑to‑commit set of Markdown files that mirror the repository’s structure. This streamlines documentation workflows, reduces manual effort, and ensures consistency across projects.

The server’s unique advantage is its bottom‑up documentation strategy, which naturally aligns with how developers think about code modules. Coupled with AI’s ability to synthesize high‑quality prose and test plans, Autodocument transforms routine repository maintenance into an automated, repeatable process that keeps documentation accurate and up‑to‑date.