Build an AI Code Documentation Generator with MCP (GitHub + Filesystem Recipe)

Documentation drifts out of date as soon as code changes. This recipe gives you an AI documentation generator that reads your repo—via GitHub or the local filesystem—and produces READMEs, API overviews, and per-module summaries.

You'll be able to ask:

• "Generate a README for this repo: purpose, setup, and main commands."
• "Document the public API of the src/api folder: list endpoints and their parameters."
• "Summarize what each file in src/utils does in one sentence."

What You'll Build

Prerequisites

Step 1: Set Up GitHub MCP

Configure GitHub MCP with a Personal Access Token (repo read scope). You'll get tools like: get_file, list_directory, search_code, list_pull_requests. Use these so the AI can read repo structure and file contents.

See our AI GitHub PR Reviewer recipe for detailed GitHub MCP setup.

Step 2: (Optional) Add Filesystem MCP for Local Repos

For local projects, add Filesystem MCP pointed at your repo root. The AI can then read files directly from disk—useful when you're not pushing to GitHub yet or want faster iteration.

Step 3: Example Prompts

• "Read the root of owner/repo and generate a README with: project name, one-paragraph description, prerequisites, install steps, and how to run tests."
• "Document every exported function in src/api: name, parameters, return type, and a one-line description."
• "List all files in src and write a short 'Module overview' section for each (2-3 sentences)."

Best Practices

• Point the AI at specific paths (e.g. src/, docs/) to keep context focused and token usage lower.
• Ask for docs in small chunks (one folder at a time) for large repos.
• Include "Do not invent endpoints or parameters; only document what exists in the code" to reduce hallucination.

Related Recipes

• Build an AI GitHub PR Reviewer
• AI-Powered File Organizer

Frequently Asked Questions