What is Devdocs Mcp

devdocs-mcp is a Model Context Protocol (MCP) server designed for documentation management and integration, inspired by devocs.io.

Use cases

Use cases for devdocs-mcp include managing API documentation, integrating documentation resources into applications, tracking issues and reviews, and ensuring documentation quality through testing.

How to use

To use devdocs-mcp, set up the project structure as outlined in the README, utilize the resource template system for URI-based access, and implement property-based tests to ensure functionality.

Key features

Key features include a resource template system with type-safe parameter handling, flexible URI template matching, comprehensive error handling, and a robust testing strategy using property-based testing.

Where to use

devdocs-mcp can be used in software development environments where documentation management and integration are crucial, such as API documentation, technical writing, and project management.

DevDocs MCP Implementation

A Model Context Protocol (MCP) implementation for documentation management and integration.

Project Structure

src/
├── resources/
│   ├── templates/      # Resource template system
│   └── managers/       # Resource management
├── documentation/
│   ├── processors/     # Documentation processing
│   └── integrators/    # Integration handlers
├── tasks/
│   ├── issues/         # Issue tracking
│   └── reviews/        # Review management
└── tests/
    ├── property/       # Property-based tests
    └── integration/    # Integration tests

Core Components

Resource Template System

The resource template system provides URI-based access to documentation resources with:

• Type-safe parameter handling through Pydantic
• Flexible URI template matching
• Comprehensive error handling
• State management for resource lifecycle

Example usage:

from src.resources.templates.base import ResourceTemplate

# Create a template with parameter typing
template = ResourceTemplate(
    uri_template='docs://api/{version}/endpoint',
    parameter_types={'version': str}
)

# Extract and validate parameters
params = template.extract_parameters('docs://api/v1/endpoint')
template.validate_parameters(params)

Testing Strategy

The project uses property-based testing with Hypothesis to ensure:

• URI template validation
• Parameter extraction correctness
• Error handling robustness
• Type safety enforcement

Run tests:

pytest tests/property/test_templates.py

Implementation Progress

Completed

• [x] Basic project structure
• [x] Resource template system
• [x] Property-based testing infrastructure
• [x] URI validation and parameter extraction
• [x] Error handling foundation

In Progress

• [ ] Documentation processor integration
• [ ] Caching layer implementation
• [ ] Task management system
• [ ] Performance optimization

Planned

• [ ] Search implementation
• [ ] Branch mapping system
• [ ] State tracking
• [ ] Monitoring system

Development Guidelines

1. Follow TDD approach:

   • Write property-based tests first
   • Implement minimal passing code
   • Refactor for clarity and efficiency

2. Error Handling:

   • Use structured error types
   • Implement recovery strategies
   • Maintain system stability

3. Documentation:

   • Keep README updated
   • Document new features
   • Include usage examples

Branch Management

The project uses a branch-based development approach for:

• Feature tracking
• Documentation integration
• Task management
• Progress monitoring

Contributing

1. Create feature branch
2. Add property tests
3. Implement feature
4. Update documentation
5. Submit pull request

Next Steps

1. Implement documentation processor integration
2. Add caching layer with proper lifecycle management
3. Develop task management system
4. Create monitoring and performance metrics

Support Resources

• MCP Concepts: mcp-docs/docs/concepts/
• Python SDK: python-sdk/src/mcp/
• Example Servers: python-sdk/examples/servers/