# Perception Tools MCP Server - Project Summary ## Overview A comprehensive MCP (Model Context Protocol) server implementing 18 perception tools organized into 5 categories, following SOLID principles with a modular architecture. ## Implementation Details ### Architecture The project follows the **Single Responsibility Principle** with separate modules for each tool category: ``` perception-tools/ ├── src/ │ ├── base.py # Shared models and utilities │ ├── search_tools.py # Search functionality (3 tools) │ ├── multimodal_tools.py # Multimodal understanding (4 tools) │ ├── filesystem_tools.py # File operations (3 tools) │ ├── public_data_tools.py # Public APIs (6 tools) │ ├── private_data_tools.py # Private data sources (2 tools) │ └── main.py # MCP server entry point ├── requirements.txt # Dependencies ├── env.example # Configuration template ├── quickstart.py # Demo script ├── test_imports.py # Module verification ├── README.md # User documentation ├── SETUP.md # Setup instructions └── TOOL_REFERENCE.md # Complete API reference ``` ### Design Principles Applied #### KISS (Keep It Simple, Stupid) - Each tool has a single, clear purpose - Simple async function signatures - Straightforward error handling #### DRY (Don't Repeat Yourself) - Common utilities in `base.py` (ActionResponse, file validation, URL downloading) - Shared error handling patterns - Reusable Pydantic models #### SOLID Principles **Single Responsibility:** - Each module handles one category of tools - Base module provides shared functionality only - Tools have single, well-defined purposes **Open/Closed:** - Easy to add new tools without modifying existing code - Extensible through new modules - MCP decorator pattern allows non-invasive tool registration **Liskov Substitution:** - All tools return consistent `ActionResponse` format - Uniform error handling across all tools **Interface Segregation:** - Tools expose only necessary parameters - Optional parameters with sensible defaults - No forced dependencies on unused features **Dependency Inversion:** - Tools depend on abstractions (ActionResponse, TextContent) - External services accessed through interfaces - Configuration via environment variables ## Tool Categories ### 1. Search Tools (3 tools) - `web_search`: Google Custom Search integration - `download`: HTTP/HTTPS file downloads with safety checks - `knowledge_base_search`: Local document search ### 2. Multimodal Understanding Tools (4 tools) - `webpage_reader`: HTML content extraction - `document_reader`: PDF/DOCX/PPTX processing - `image_parser`: Image analysis with PIL - `video_parser`: Video metadata extraction with OpenCV ### 3. File System Tools (3 tools) - `file_reader`: File reading with encoding support - `grep`: Regex pattern search in files - `text_summarizer`: Text summarization (extractive/LLM) ### 4. Public Data Source Tools (6 tools) - `weather`: OpenWeather API integration - `stock_price`: Yahoo Finance data - `currency_converter`: Exchange rate conversion - `wikipedia_search`: Wikipedia API wrapper - `arxiv_search`: Academic paper search - `wayback_search`: Internet Archive access ### 5. Private Data Source Tools (2 tools) - `calendar_events`: Google Calendar OAuth2 integration - `notion_search`: Notion API wrapper ## Key Features ### Error Handling - Consistent error response format - Detailed error types for debugging - Graceful degradation when services unavailable ### Configuration Management - Environment variable based configuration - Template file for easy setup - Optional dependencies clearly marked ### Response Format All tools return standardized JSON responses: ```json { "success": true/false, "message": "Result data or error message", "metadata": { "additional": "context information" } } ``` ### Safety Features - File size limits for downloads - Timeout controls for network operations - Path validation to prevent directory traversal - URL validation for external requests ## Testing ### Import Verification ```bash python test_imports.py ``` ### Functional Testing ```bash python quickstart.py ``` ### Manual MCP Server Testing ```bash cd src && python main.py ``` ## Dependencies ### Core - `mcp`: MCP server framework - `pydantic`: Data validation - `python-dotenv`: Configuration management - `requests`: HTTP client ### Document Processing - `PyPDF2`: PDF parsing - `python-docx`: Word documents - `python-pptx`: PowerPoint presentations - `Pillow`: Image processing - `opencv-python`: Video processing ### Web Scraping - `beautifulsoup4`: HTML parsing - `lxml`: XML/HTML parser ### Data Sources - `wikipedia`: Wikipedia API - `arxiv`: ArXiv API ### Optional - Google Calendar: `google-auth-*`, `google-api-python-client` - Notion: `notion-client` ## Configuration Requirements ### Required for Full Functionality - `GOOGLE_API_KEY`: For web search - `GOOGLE_CSE_ID`: For web search - `OPENWEATHER_API_KEY`: For weather data ### Optional - `NOTION_API_KEY`: For Notion integration - Google OAuth2 credentials: For Calendar integration ## Performance Considerations - Default timeouts: 30-180 seconds depending on operation - File size limits: 100MB for downloads, 500MB for videos - Text truncation: 50,000 characters for file reading - Result limits: Configurable per tool (typically 5-10 items) ## Future Enhancements Potential additions: 1. LLM-based summarization integration 2. Image analysis with vision APIs 3. Video frame extraction and analysis 4. Database search integration 5. Email integration (Gmail, Outlook) 6. Slack/Discord integration 7. GitHub API integration 8. Real-time data streaming support ## MCP Integration The server uses the MCP SDK v2 `MCPServer` with stdio transport, making it compatible with: - Claude Desktop - Other MCP-compatible clients - Custom integration via stdio communication ## Documentation Comprehensive documentation provided: - `README.md`: Overview and quick start - `SETUP.md`: Detailed setup instructions - `TOOL_REFERENCE.md`: Complete API reference for all 18 tools - `PROJECT_SUMMARY.md`: This file ## Code Quality - Type hints throughout - Comprehensive docstrings - Consistent formatting - Error handling at all levels - Logging for debugging ## Maintenance To add new tools: 1. Create function in appropriate module 2. Follow existing patterns (async, ActionResponse) 3. Register in `main.py` with `@mcp.tool` decorator 4. Update documentation ## Success Metrics ✅ 18 tools implemented across 5 categories ✅ Modular architecture following SOLID principles ✅ Comprehensive error handling ✅ Complete documentation ✅ Easy configuration and setup ✅ MCP-compatible server ready for production use ## Status **Implementation: Complete** **Documentation: Complete** **Testing Framework: Complete** **Ready for Use: Yes (with dependency installation)**