MCP Docs Tools

Overview

The MCP Docs Tools server is a lightweight Node.js application that exposes three specialized documentation generators for Python projects via the Model Context Protocol. It solves a common pain point for developers and AI assistants: automatically producing up‑to‑date, machine‑readable documentation without manual effort. By integrating directly into an MCP workflow, the server lets AI assistants like Claude or GPT‑4 request fresh class diagrams, directory trees, and function signatures on demand, enabling dynamic code analysis and continuous documentation pipelines.

At its core, the server orchestrates a hybrid architecture. Node.js handles MCP communication and command routing while delegating heavy‑lifting to Python’s Abstract Syntax Tree (AST) module. This split allows the server to run on any platform that supports Node.js, while still leveraging Python’s introspection capabilities for accurate parsing. The server automatically locates a suitable Python 3 interpreter, with fallbacks for Windows (), macOS/Linux (, then ). If no interpreter is found, it provides a clear error message and optional environment variables (, ) for custom overrides.

Key Features

• Zero‑Configuration Operation: Launch the server with a single command; it discovers project paths, Python interpreters, and output locations without additional setup.
• Smart Exclusions: When generating directory trees or class diagrams, the tools ignore common build artifacts (e.g., , virtual environments) and IDE metadata, producing clean, readable output.
• Rich UML Output: produces PlantUML syntax that captures class inheritance, public/private members, decorators, type hints, and docstrings. This output can be rendered by any PlantUML tool or embedded directly in documentation sites.
• Concise Directory Visualization: outputs a Unicode box‑drawing tree that mirrors the actual filesystem layout, aiding navigation and onboarding.
• Function Signature Documentation: lists module‑level functions with full signatures, decorators, and type hints, making it easier to understand API contracts at a glance.

Use Cases

• AI‑Driven Code Review: An assistant can request the latest class diagram for a module, providing visual context during a review session.
• Continuous Documentation: CI pipelines can invoke the MCP server to regenerate documentation artifacts whenever code changes, ensuring that docs stay in sync with the repository.
• Onboarding New Developers: New team members can ask an AI helper to produce a tree view of the project or list all functions in a module, accelerating their learning curve.
• Educational Tools: Interactive coding platforms can expose these tools to students, letting them see UML diagrams or function signatures instantly as they write code.

Integration with AI Workflows

Because the server communicates over stdin/stdout following MCP, any client that implements the protocol can call its three tools as if they were native functions. The AI assistant supplies a JSON payload with the required , and receives structured output files (, ) that can be read back into the conversation. This seamless interaction eliminates manual file handling, enabling fully automated documentation generation as part of a larger AI‑powered development workflow.

Standout Advantages

• Cross‑Language Compatibility: While the tools target Python, the MCP interface allows future expansion to other languages without changing client logic.
• Modular Design: Each tool is a discrete function, making it easy to extend or replace individual components.
• Platform Agnostic: The server runs wherever Node.js is available, and the Python dependency is automatically resolved, reducing friction for diverse development environments.

In summary, MCP Docs Tools empowers developers and AI assistants to generate precise, machine‑readable documentation on demand. Its zero‑configuration, smart exclusion logic, and rich PlantUML output make it a valuable addition to any AI‑augmented coding ecosystem.