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securityF
license-
qualityA Model Context Protocol server utilizing Claude AI for generating intelligent queries and offering documentation assistance based on API documentation analysis.
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Used for property-based testing to ensure URI template validation, parameter extraction correctness, error handling robustness, and type safety enforcement
Provides type-safe parameter handling for the resource template system, enabling validation and extraction of parameters from URIs
Supports the testing infrastructure, allowing for property-based and integration tests to validate the functionality of the documentation management system
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
Basic project structure
Resource template system
Property-based testing infrastructure
URI validation and parameter extraction
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/
This server cannot be installed
A Model Context Protocol implementation that enables AI-powered access to documentation resources, featuring URI-based navigation, template matching, and structured documentation management.
- Project Structure
- Core Components
- Implementation Progress
- Development Guidelines
- Branch Management
- Contributing
- Next Steps
- Support Resources
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