DevDocs MCP
A Model Context Protocol implementation that enables AI-powered access to documentation resources, featuring URI-based navigation, template matching, and structured documentation management.
llmian-space
README
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
-
Follow TDD approach:
- Write property-based tests first
- Implement minimal passing code
- Refactor for clarity and efficiency
-
Error Handling:
- Use structured error types
- Implement recovery strategies
- Maintain system stability
-
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
- Create feature branch
- Add property tests
- Implement feature
- Update documentation
- Submit pull request
Next Steps
- Implement documentation processor integration
- Add caching layer with proper lifecycle management
- Develop task management system
- 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/
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