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MCP Docs Tools

MCP Docs Tools

Local
github.com/osokMemory & Knowledge2Updated 57w ago

About MCP Docs Tools

MCP Docs Tools is a Node.js server for generating documentation from Python projects. It provides focused tools for class diagrams, directory trees, and module-level function references for developers and AI assistants.

Key features

  1. 01Generate PlantUML class diagrams
  2. 02Create directory tree documentation
  3. 03Document module-level function signatures
  4. 04Capture decorators and type hints
  5. 05Exclude common generated and IDE files

Use cases

  1. 01Mapping class relationships in a Python project
  2. 02Recording a project's directory structure
  3. 03Building a reference for module functions

MCP support

The MCP server exposes three Python project documentation tools to MCP clients: class diagram, tree structure, and module function generation.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Docs Tools

A Node.js-based MCP (Model Context Protocol) tool server that provides three focused documentation generation tools for Python projects. Built as an npm package that can be installed directly from the Git repository.

Features

🔧 Three Powerful Tools
  1. create_class_diagram - Analyzes Python files and generates UML class diagrams in PlantUML format
  2. create_tree_structure - Creates clean directory tree structure documentation with smart exclusions
  3. create_module_functions - Documents module-level functions with signatures, decorators, and type hints
🚀 Key Benefits
  • Zero Configuration: Works out of the box with sensible defaults
  • Smart Exclusions: Automatically filters out cache, build, and IDE files
  • Rich Documentation: Captures type hints, decorators, docstrings, and inheritance
  • MCP Integration: Seamlessly integrates with AI assistants via Model Context Protocol
  • Hybrid Architecture: Node.js orchestration + Python AST parsing for reliability

Installation

From Git Repository (Recommended)
# Clone the repository
git clone https://github.com/your-username/mcp-docs-tools.git
cd mcp-docs-tools

# Install dependencies
npm install

# Install globally (optional)
npm install -g .

# Or run directly
npm start
Direct Installation from Git
# Install directly from GitHub
npm install -g git+https://github.com/your-username/mcp-docs-tools.git

# Then run
mcp-docs-tools
Local Development
git clone https://github.com/your-username/mcp-docs-tools.git
cd mcp-docs-tools
npm install
npm start

Requirements

  • Node.js ≥18.0.0
  • Python 3.x (for AST parsing)
  • Git (for cloning the repository)

Python Interpreter Detection and Windows Support

The server automatically detects a working Python 3 interpreter at runtime. On Windows it prefers py -3 when available, and falls back to python or python3 if they resolve to Python 3. On macOS/Linux it prefers python3, then falls back to python if it is Python 3.

If no Python 3 interpreter is found, you will see an actionable error:

"Python 3 interpreter not found. Install Python 3 or set MCP_PYTHON (and optional MCP_PYTHON_ARGS). Tried: ..."

Environment Overrides (optional)

You can explicitly specify the interpreter and arguments:

  • MCP_PYTHON: command or absolute path (e.g., py, python3, C:\\Python312\\python.exe)
  • MCP_PYTHON_ARGS: space-separated arguments (e.g., -3)

Examples:

# Windows PowerShell
$env:MCP_PYTHON = "python"
$env:MCP_PYTHON_ARGS = "-3"
npm start
# macOS/Linux bash
export MCP_PYTHON=py
export MCP_PYTHON_ARGS=-3
npm start

Usage

As MCP Server

Start the server to expose tools via Model Context Protocol:

# If installed globally
mcp-docs-tools

# Or from the project directory
npm start

# Or run directly with node
node bin/server.js

The server will listen on stdin/stdout and expose three tools that can be called by MCP clients.

Tool Specifications
1. create_class_diagram

Purpose: Generate UML class diagrams from Python code

Parameters:

  • project_path (string, required): Root path of the Python project to analyze

Output:

  • File: docs/uml.txt
  • Format: PlantUML syntax
  • Content: Classes with public/private methods, attributes, and inheritance relationships

Example:

@startuml
class MyClass {
  +public_attr: str
  -_private_attr: int
  --
  +__init__(self, name: str)
  +public_method(self, arg: int): bool
  -{static} _private_method(): None
}
@enduml
2. create_tree_structure

Purpose: Generate project directory tree structure

Parameters:

  • project_path (string, required): Root path of the project to analyze

Output:

  • File: docs/tree-structure.txt
  • Format: Unicode box-drawing tree
  • Content: Complete file/directory structure with smart exclusions

Example:

my-project
├── src/
│   ├── main.py
│   └── utils/
│       └── helpers.py
├── tests/
│   └── test_main.py
└── README.md
3. create_module_functions

Purpose: Document module-level functions and signatures

Parameters:

  • project_path (string, required): Root path of the Python project to analyze

Output:

  • File: docs/module-functions.txt
  • Format: Hierarchical markdown documentation
  • Content: Functions organized by module with full signatures, decorators, and docstrings

Example:

## Module: src.utils.helpers

### `async def process_data(data: List[str], timeout: int = 30) -> Dict[str, Any]`

**Decorators:**
- `@retry(max_attempts=3)`

**Description:**
Process a list of data items with optional timeout.

**Line:** 42

Architecture

Hybrid Node.js + Python Approach

The tool uses a hybrid architecture that combines the best of both worlds:

  • Node.js Server: Handles MCP protocol, tool registration, and process orchestration
  • Python Scripts: Perform robust AST parsing and documentation generation
  • Clean Separation: Protocol handling separate from parsing logic
Project Structure
mcp-docs-tools/
├── package.json              # npm package configuration
├── bin/
│   └── server.js             # Main MCP server entry point
├── src/
│   ├── server.js             # MCP server implementation
│   ├── tools/                # Tool implementations
│   │   ├── class-diagram.js  # UML generation wrapper
│   │   ├── tree-structure.js # Tree generation wrapper
│   │   └── module-functions.js # Function docs wrapper
│   └── config/
│       └── exclusions.js     # Default exclusion patterns
├── python/
│   ├── generate_uml.py       # Python AST parsing for classes
│   ├── generate_tree.py      # Directory tree generation
│   ├── generate_functions.py # Function parsing and documentation
│   └── requirements.txt      # Python dependencies (none needed)
└── README.md

Smart Exclusions

The tools automatically exclude common files and directories that shouldn't be documented:

Python
  • __pycache__, *.pyc, *.pyo, *.pyd
  • build, dist, eggs, *.egg-info
  • Virtual environments: venv, .venv, env, virtualenv
Development Tools
  • Version control: .git, .svn, .hg
  • IDEs: .idea, .vscode, .cursor
  • Testing: .pytest_cache, .coverage, .tox
Build & Package Managers
  • node_modules, target, out, bin
  • package-lock.json, yarn.lock, Pipfile.lock
OS & Temporary
  • .DS_Store, Thumbs.db, *.tmp, *.log

Integration with AI Assistants

Cursor IDE

The configuration depends on how you installed the tools:

Option A: If you cloned the repository (Recommended method)

Create a .cursorrules file in your projects and add this to your Cursor MCP configuration:

{
  "mcpServers": {
    "docs-tools": {
      "command": "node",
      "args": ["/path/to/mcp-docs-tools/bin/server.js"],
      "cwd": "/path/to/mcp-docs-tools"
    }
  }
}

Replace /path/to/mcp-docs-tools with the actual path where you cloned the repository.

For example:

  • macOS/Linux: "/Users/yourname/projects/mcp-docs-tools"
  • Windows: "C:\\Users\\yourname\\projects\\mcp-docs-tools"
Option B: If you installed globally with npm install -g
{
  "mcpServers": {
    "docs-tools": {
      "command": "mcp-docs-tools"
    }
  }
}
.cursorrules file content (for any installation method)

Create this .cursorrules file in your Python projects:

# Documentation Tools Integration

## Available MCP Tools
- `create_class_diagram` - Generate UML class diagrams  
- `create_tree_structure` - Generate directory tree
- `create_module_functions` - Document module functions

## Usage
Run these tools at session start to generate documentation in `docs/` directory.
Reference the generated files to understand codebase structure.

## Generated Files
- `docs/uml.txt` - PlantUML class diagrams
- `docs/tree-structure.txt` - Directory structure  
- `docs/module-functions.txt` - Function documentation
Claude Desktop
Option A: If you cloned the repository (Recommended method)

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "docs-tools": {
      "command": "node",
      "args": ["/path/to/mcp-docs-tools/bin/server.js"],
      "cwd": "/path/to/mcp-docs-tools"
    }
  }
}

Replace /path/to/mcp-docs-tools with the actual path where you cloned the repository.

Option B: If you installed globally with npm install -g
{
  "mcpServers": {
    "docs-tools": {
      "command": "mcp-docs-tools"
    }
  }
}
Quick Setup Guide
  1. Clone and install (recommended):

    git clone https://github.com/your-username/mcp-docs-tools.git
    cd mcp-docs-tools
    npm install
    
  2. Find your installation path:

    pwd
    # Copy this path for your MCP configuration
    
  3. Update your MCP config with the path from step 2

  4. Test the tools in your Python projects!

Error Handling

The tools include comprehensive error handling:

  • Python Process Failures: Detailed error messages with stdout/stderr
  • Missing Dependencies: Clear instructions for Python installation
  • File Permission Issues: Graceful handling with informative messages
  • Invalid Project Paths: Path validation before processing

Performance

  • Lightweight: Minimal memory footprint with short-lived Python processes
  • Fast: Efficient AST parsing with smart file filtering
  • Scalable: Handles large codebases with thousands of files
  • Concurrent: Multiple tools can run simultaneously

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

License

MIT License - see LICENSE file for details.

Support

  • Issues: Report bugs and feature requests on GitHub
  • Documentation: Full API documentation available in the repository
  • Examples: Sample projects and usage patterns in the examples directory

Made with ❤️ for the Python development community

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