asset-aware-mcp 0.1.1

Medical RAG with Asset-Aware MCP - Precise PDF asset retrieval (tables, figures, sections) for AI Agents

asset-aware-mcp

🏥 Medical RAG with Asset-Aware MCP - 讓 AI Agent 精準存取 PDF 文獻中的表格、章節與知識圖譜

🌐 繁體中文

✨ Features

• 📄 Asset-Aware ETL - PDF → Markdown, using PyMuPDF to automatically identify tables, sections, and images
• 🔄 Async Job Pipeline - Supports asynchronous task processing, tracking progress for large documents
• 🗺️ Document Manifest - Structured list, allowing Agents to "see the map" before precisely accessing data
• 🧠 LightRAG Integration - Knowledge Graph + Vector Index, supporting cross-document comparison and reasoning
• 🔌 MCP Server - Exposes tools and resources to Copilot/Claude via FastMCP
• 🏥 Medical Research Focus - Optimized for medical literature, supporting Base64 image transmission for Vision AI analysis

🏗️ Architecture

┌─────────────────────────────────────────────────────────┐
│                    AI Agent (Copilot)                   │
└─────────────────────┬───────────────────────────────────┘
                      │ MCP Protocol (Tools & Resources)
┌─────────────────────▼───────────────────────────────────┐
│                 MCP Server (server.py)                  │
│  ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐   │
│  │   ingest    │ │  inspect    │ │     fetch       │   │
│  │  documents  │ │  manifest   │ │     asset       │   │
│  └─────────────┘ └─────────────┘ └─────────────────┘   │
│  ┌─────────────────────────────────────────────────┐   │
│  │          consult_knowledge_graph                │   │
│  └─────────────────────────────────────────────────┘   │
└─────────────────────┬───────────────────────────────────┘
                      │
┌─────────────────────▼───────────────────────────────────┐
│                  ETL Pipeline (DDD)                     │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐              │
│  │ PyMuPDF  │  │  Asset   │  │ LightRAG │              │
│  │ Adapter  │→ │  Parser  │→ │  Index   │              │
│  └──────────┘  └──────────┘  └──────────┘              │
└─────────────────────┬───────────────────────────────────┘
                      │
┌─────────────────────▼───────────────────────────────────┐
│                   Local Storage                         │
│  ./data/                                                │
│  ├── doc_{id}/                                          │
│  │   ├── full.md          # Markdown Content            │
│  │   ├── manifest.json    # Asset Map                   │
│  │   └── images/          # Extracted Figures           │
│  └── lightrag/            # Knowledge Graph             │
└─────────────────────────────────────────────────────────┘

📁 Project Structure (DDD)

asset-aware-mcp/
├── src/
│   ├── domain/              # 🔵 Domain: Entities, Value Objects, Interfaces
│   ├── application/         # 🟢 Application: Doc Service, Job Service, Asset Service
│   ├── infrastructure/      # 🟠 Infrastructure: PyMuPDF, LightRAG, File Storage
│   └── presentation/        # 🔴 Presentation: MCP Server (FastMCP)
├── data/                    # Document and Asset Storage
├── docs/
│   └── spec.md              # Technical Specification
├── tests/                   # Unit and Integration Tests
├── vscode-extension/        # VS Code Management Extension
└── pyproject.toml           # uv Project Config

🚀 Quick Start

# Install dependencies (using uv)
uv sync

# Run MCP Server
uv run python -m src.presentation.server

# Or use the VS Code extension for graphical management

🔌 MCP Tools

Tool	Purpose
ingest_documents	匯入 PDF，觸發 ETL pipeline (支援 async)
get_job_status	檢查 ETL 任務進度
list_documents	列出所有已處理的文件
inspect_document_manifest	查看文件結構地圖 (表格/圖片/章節)
fetch_document_asset	精準取得表格 (MD) / 圖片 (B64) / 章節
consult_knowledge_graph	知識圖譜查詢，跨文獻比較

🔧 Tech Stack

Category	Technology
Language	Python 3.10+
ETL	PyMuPDF (fitz)
RAG	LightRAG (lightrag-hku)
MCP	FastMCP
Storage	Local filesystem (JSON/Markdown/PNG)

📋 Documentation

• Technical Spec - 詳細技術規格
• Architecture - 系統架構
• Constitution - 專案原則

📄 License

Apache License 2.0