Summary
Automates documentation generation across five distinct tools: JSDoc comment creation from function signatures, README completeness analysis with scoring, changelog generation from git commits following Keep a Changelog format, REST API documentation from endpoint definitions, and code comment coverage analysis that surfaces TODOs and undocumented functions. Runs over stdio and requires no configuration. Reach for this when you need structured documentation output during development workflows, especially if you're working with AI agents that need to generate or evaluate docs programmatically. The analyze_readme tool rates completeness 0-100 and flags missing sections, while generate_api_docs handles request/response examples and status codes automatically.
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mcp-docs-tools
Documentation generation tools for AI agents, served via the Model Context Protocol (MCP).
Overview
mcp-docs-tools provides five specialized documentation tools accessible through MCP:
| Tool | Description |
|---|---|
generate_jsdoc | Generate JSDoc/TSDoc comments from function signatures |
analyze_readme | Analyze README completeness and suggest improvements |
generate_changelog | Generate CHANGELOG entries from commit messages |
generate_api_docs | Generate REST API documentation from endpoint definitions |
analyze_code_comments | Analyze comment coverage, find TODOs, detect undocumented functions |
Installation
npm install
npm run build
Usage
As an MCP Server
Add to your MCP client configuration:
{
"mcpServers": {
"docs-tools": {
"command": "node",
"args": ["path/to/mcp-docs-tools/dist/index.js"]
}
}
}
Tools
generate_jsdoc
Parses a function signature and generates JSDoc/TSDoc with @param, @returns, @throws, and @example tags.
Parameters:
functionSignature(string, required) - The function signature to documentdescription(string, optional) - Description of the functionincludeExample(boolean, optional, default: true) - Whether to include an@exampletag
analyze_readme
Analyzes README content for required sections (Installation, Usage, License, etc.), rates completeness from 0-100, and suggests missing sections.
Parameters:
content(string, required) - Full text content of the README file
generate_changelog
Generates CHANGELOG entries from git-style commit messages following the Keep a Changelog format. Categorizes commits as Added, Changed, Fixed, Removed, Deprecated, or Security.
Parameters:
versions(array, required) - Array of{ version, date, commits }objectsprojectName(string, optional) - Project name for the header
generate_api_docs
Generates REST API documentation in Markdown from endpoint descriptions including method, URL, parameters, request/response examples, and status codes.
Parameters:
apiTitle(string, required) - Title for the API documentationbaseUrl(string, optional) - Base URL for the APIapiDescription(string, optional) - General API descriptionendpoints(array, required) - Array of endpoint definitions
analyze_code_comments
Analyzes source code comment coverage: computes comment-to-code ratio, finds TODO/FIXME/HACK markers, detects functions without documentation, and suggests where docs are needed.
Parameters:
code(string, required) - Source code to analyzelanguage(string, optional, default: "typescript") - Programming language
Configuration
No additional configuration required. The server runs over stdio.
License
MIT
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Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
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