This MCP server provides a comprehensive implementation of the Model Context Protocol for documentation management and integration, allowing efficient resource handling through URI-based access with type safety and parameter validation.
To install the DevDocs MCP Implementation, follow these steps:
Clone the repository:
git clone https://github.com/your-username/devdocs-mcp.git
cd devdocs-mcp
Install the required dependencies:
pip install -r requirements.txt
Verify the installation by running the tests:
pytest tests/property/test_templates.py
The resource template system is the foundation of the MCP implementation, providing URI-based access to documentation resources.
Key features:
You can create and use resource templates as follows:
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 from a URI
params = template.extract_parameters('docs://api/v1/endpoint')
template.validate_parameters(params)
To access documentation resources using the MCP implementation:
Example:
# Create a template for API documentation
api_docs_template = ResourceTemplate(
uri_template='docs://api/{version}/{endpoint}',
parameter_types={'version': str, 'endpoint': str}
)
# Access a specific API endpoint documentation
params = api_docs_template.extract_parameters('docs://api/v2/authentication')
if api_docs_template.validate_parameters(params):
# Use params to fetch the documentation
documentation = fetch_documentation(params['version'], params['endpoint'])
The MCP implementation provides structured error handling for various situations:
Example of error handling:
try:
params = template.extract_parameters('docs://api/invalid-endpoint')
template.validate_parameters(params)
except ValueError as e:
print(f"Parameter validation error: {e}")
except ResourceNotFoundError as e:
print(f"Resource not found: {e}")
The MCP implementation comes with a robust testing framework:
# Run all tests
pytest
# Run specific test categories
pytest tests/property/
pytest tests/integration/
The current implementation includes:
Features in development that will be available soon:
To add this MCP server to Claude Code, run this command in your terminal:
claude mcp add-json "devdocs" '{"command":"npx","args":["-y","devdocs-mcp"]}'
See the official Claude Code MCP documentation for more details.
There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json
file so that it is available in all of your projects.
If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json
file.
To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".
When you click that button the ~/.cursor/mcp.json
file will be opened and you can add your server like this:
{
"mcpServers": {
"devdocs": {
"command": "npx",
"args": [
"-y",
"devdocs-mcp"
]
}
}
}
To add an MCP server to a project you can create a new .cursor/mcp.json
file or add it to the existing one. This will look exactly the same as the global MCP server example above.
Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.
The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.
You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.
To add this MCP server to Claude Desktop:
1. Find your configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json
%APPDATA%\Claude\claude_desktop_config.json
~/.config/Claude/claude_desktop_config.json
2. Add this to your configuration file:
{
"mcpServers": {
"devdocs": {
"command": "npx",
"args": [
"-y",
"devdocs-mcp"
]
}
}
}
3. Restart Claude Desktop for the changes to take effect