What is Mcp Pif V3

MCP-PIF-v3 is a comprehensive personal knowledge management system that integrates a Knowledge Graph, RAG Pipeline, Obsidian integration, and a desktop application to organize, analyze, and retrieve information effectively.

Use cases

Use cases include managing personal notes and documents, conducting research with advanced retrieval techniques, visualizing knowledge graphs for better understanding, and integrating with other tools for enhanced productivity.

How to use

To use MCP-PIF-v3, ensure you have Node.js 16.x or higher, at least 4GB of RAM, and 1GB of free disk space. Install the application by running the master start script ‘start-mcp-pif.bat’ which sets up necessary directories and launches the application.

Key features

Key features include entity management with natural language queries, an inference engine for discovering relationships, document processing with semantic search capabilities, and a unified desktop application that works offline and across multiple platforms.

Where to use

MCP-PIF-v3 can be used in various fields such as personal knowledge management, academic research, content creation, and any domain that requires efficient organization and retrieval of information.

MCP-PIF - Master Control Program - Personal Information Framework

Overview

MCP-PIF is a comprehensive personal knowledge management system that combines:

1. Knowledge Graph - Manage entities and relationships with natural language queries and inference
2. RAG Pipeline - Process documents with advanced retrieval-augmented generation
3. Obsidian Integration - Visualize knowledge in the Obsidian note-taking app
4. Desktop Application - Access all features through a unified interface

The system is designed to organize, analyze, and retrieve information from personal knowledge bases, documents, and notes.

Features

Knowledge Graph

• Entity Management - Create, update, and organize entities and relationships
• Natural Language Queries - Ask questions in plain English
• Inference Engine - Automatically discover new relationships through logical rules
• Visualization - Interactive graph visualization with filtering and exploration

RAG Pipeline

• Document Processing - Extract text and metadata from various document formats
• Vector Embeddings - Create semantic embeddings of document chunks
• Semantic Search - Find relevant information based on meaning, not just keywords
• Context-Aware Generation - Generate responses with awareness of your knowledge base

Desktop Application

• Unified Interface - Access all features through a single application
• Cross-Platform - Works on Windows, macOS, and Linux
• Offline Capability - Core features work without an internet connection
• Integration Hub - Connect with other tools and services

Getting Started

Prerequisites

• Node.js 16.x or higher
• 4GB RAM minimum (8GB+ recommended)
• 1GB free disk space

Installation

Option 1: Quick Start (Windows)

Run the master start script:

start-mcp-pif.bat

This will:

1. Create necessary data directories
2. Start the Knowledge Graph server
3. Launch the desktop application

Option 2: Building the Desktop App

To build a standalone desktop application:

node build-desktop-app.js

This will create a dist directory with the packaged application. See DESKTOP-APP-GUIDE.md for more details.

Option 3: Running Individual Components

Each component can be run independently:

• Knowledge Graph Server: start-kg-server.bat
• Desktop Development Mode: run-desktop-app.bat

Usage

Knowledge Graph

1. Launch the application
2. Navigate to the “Knowledge Graph” tab
3. Add entities and relationships or import existing data
4. Use the natural language query box to ask questions
5. Run inference to discover new relationships

Example queries:

• “Who knows Alice?”
• “Find all developers who work for Acme Corp”
• “What are the connections between Bob and Charlie?”

Document Processing

1. Upload or drag documents into the application
2. The system will automatically process and index them
3. Use the search to find information across all documents
4. View connections between documents and knowledge graph entities

Directory Structure

• src/ - Core components
  • knowledge-graph/ - Knowledge Graph implementation
  • rag/ - RAG Pipeline implementation
• 05-Application/ - Desktop application
  • electron/ - Electron main process
  • frontend/ - React frontend
  • backend/ - Express backend services
• data/ - Data storage (created on first run)
  • graph-db/ - Knowledge Graph data
  • vectors/ - Vector embeddings
  • logs/ - Log files

Documentation

• DESKTOP-APP-GUIDE.md - Detailed guide for the desktop application
• 000-DOCUMENTATION_HUB/ - Comprehensive documentation
• 2025-03-22_MCP-PIF_TASK_LIST.md - Development task list

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.