PT-MCP (Paul Test Man Context Protocol)
"Where am I now?"
Named after Paul Marcarelli, the Verizon "Test Man" who famously traversed America asking "Can you hear me now?", PT-MCP asks the essential question for AI coding assistants: "Where am I now?" - providing comprehensive context understanding through integrated knowledge graphs and semantic schemas.
The Paul Test Man Story
Just as Paul Test Man mapped Verizon's network coverage across America to ensure clear communication, PT-MCP maps your codebase's semantic landscape to ensure clear understanding. The server doesn't just return code structure - it returns meaning through:
YAGO 4.5 Knowledge Graphs: Base knowledge graph segments relevant to your context
Schema.org Domain Graphs: Domain-specific semantic understanding
Codebase Analysis: Comprehensive structure, patterns, and relationships
Overview
PT-MCP helps AI coding assistants understand your codebase by providing:
Comprehensive codebase analysis - File structure, language distribution, code metrics
Context file generation - Multiple format support (.cursorrules, SPEC.md, etc.)
Incremental updates - Efficient context regeneration based on changes
Pattern extraction - Identify architectural and coding patterns
Dependency analysis - Map internal and external dependencies
API surface extraction - Document public interfaces
Context validation - Ensure accuracy and completeness
Installation
Usage
As an MCP Server
Add to your Claude Code configuration (~/.config/claude/config.json):
Available Tools
1. analyze_codebase
Perform comprehensive codebase analysis including structure, dependencies, and metrics.
Example:
Returns:
Total files, lines, and size
Language distribution with percentages
Directory structure and depth
Entry points identification
Package information (if available)
2. generate_context
Generate context files in specified format.
Note: Implementation pending (stub currently returns placeholder)
3. update_context
Incrementally update existing context files based on code changes.
Note: Implementation pending (stub currently returns placeholder)
4. extract_patterns
Identify and extract architectural and coding patterns.
Note: Implementation pending (stub currently returns placeholder)
5. analyze_dependencies
Analyze and map internal and external dependencies.
Note: Implementation pending (stub currently returns placeholder)
6. watch_project
Start monitoring project for changes and auto-update context.
Note: Implementation pending (stub currently returns placeholder)
7. extract_api_surface
Extract and document public API surface.
Note: Implementation pending (stub currently returns placeholder)
8. validate_context
Validate accuracy and completeness of generated context files.
Note: Implementation pending (stub currently returns placeholder)
Available Resources
context://project/{path}
Current project context including structure, patterns, and dependencies.
context://patterns/{path}
Architectural and coding patterns detected in the codebase.
context://dependencies/{path}
Internal and external dependency relationships.
Development Status
Phase 1: Foundation (β Complete)
MCP server boilerplate with stdio transport
Project structure and dependencies
analyze_codebasetool - fully functionalStub implementations for remaining tools
Phase 2: Core Analysis (π§ In Progress)
Implement
generate_contexttoolImplement
extract_patternstoolImplement
analyze_dependenciestoolAdd tree-sitter integration for deep code analysis
Phase 3: Advanced Features (π Planned)
Implement
update_contexttool with incremental updatesImplement
watch_projecttool with file system monitoringImplement
extract_api_surfacetoolImplement
validate_contexttool
Architecture
Testing
Test the MCP server locally:
Contributing
This is a work in progress. See the specification document for the full implementation roadmap.
Next Steps
Implement context file generators for different formats
Add tree-sitter integration for deeper code analysis
Implement pattern extraction algorithms
Add file system watching and incremental updates
Create comprehensive test suite
License
MIT
Related Projects
Giga AI - VS Code extension for context management
Kilo Code CLI - CLI wrapper for VS Code extensions
Model Context Protocol - Protocol specification