Enhanced MCP Server Implementation with Comprehensive Documentation and Examples

[Copilot]

This pull request significantly improves the MCP (Model Context Protocol) server functionality by enhancing the example implementation and documentation to provide users with a clear, production-ready starting point for utilizing Helix's MCP capabilities.

Enhanced Example Implementation

The examples/mcp_server.py file has been completely rewritten to provide:

• Comprehensive documentation with detailed docstrings explaining MCP server setup and usage
• Multiple execution modes with clear examples for synchronous, asynchronous, and background execution
• Configurable tool management showing how to enable/disable specific MCP tools based on requirements
• Production-ready structure with proper error handling and configuration management
• Claude Desktop integration guide with exact configuration snippets

Before:

# Simple example with minimal documentation
mcp_server = MCPServer("helix-mcp", helix_client, tool_config=tool_config)
mcp_server.run_bg()

After:

def create_tool_config(
    disable_search_vector_text: bool = False,
    disable_keyword_search: bool = False,
    disable_filters: bool = False
) -> ToolConfig:
    """Create a tool configuration with optional tool disabling."""
    return ToolConfig(
        search_vector_text=not disable_search_vector_text,
        search_keyword=not disable_keyword_search,
        filter_items=not disable_filters,
        # ... comprehensive configuration
    )

Improved Documentation

The README.md MCP section has been completely rewritten to include:

• Quick start guide with minimal setup code
• Complete API overview documenting all 15+ available MCP tools
• Tool categories explaining graph traversal, search, filtering, and data access capabilities
• Execution mode examples showing all three ways to run the server
• Integration instructions for popular AI platforms

Key improvements:

• Added documentation for all MCP tools (out_step, in_step, search_vector, filter_items, etc.)
• Explained tool configuration options and use cases
• Provided complete Claude Desktop integration example
• Added code examples for each execution mode

Benefits for Users

1. Clear Starting Point: Users can now easily understand how to set up and configure an MCP server
2. Flexible Configuration: Detailed examples show how to customize which tools are available
3. Production Guidance: The enhanced example includes proper error handling and configuration patterns
4. AI Integration: Clear instructions for connecting to popular AI platforms like Claude Desktop

Technical Details

• File Changes: Enhanced examples/mcp_server.py (25 → 120+ lines) and README.md MCP section
• Backward Compatibility: All existing functionality remains unchanged
• Testing: Verified imports, tool configuration, and example execution work correctly
• Documentation: Added comprehensive inline documentation and usage examples

The existing helix/mcp.py implementation and helix/__init__.py exports remain unchanged, ensuring full backward compatibility while providing much better user experience through improved examples and documentation.

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