Easy MCP RAG 🚀

A high-performance Model Context Protocol (MCP) server for RAG using Qdrant. Built for UV/UVX with CPU/GPU support and HTTP transport.

✨ Features

🔍 Automatic Document Indexing - Scan directories and index all documents
📁 Smart Organization - Each subdirectory becomes its own searchable dataset
🛠️ Dynamic MCP Tools - Auto-generated tools for each collection
📄 Multi-Format Support - PDF, DOCX, CSV, XLSX, TXT, Markdown, and more
⚡ GPU Acceleration - Optional CUDA/MPS support for faster embeddings
🌐 HTTP Transport - Run as HTTP server or stdio
📦 UV/UVX Ready - Install and run with a single command
📊 Verbose Logging - Detailed query tracking and monitoring

🚀 Quick Start

Install with UVX (Recommended)

Run directly from GitHub without installation:

uvx --from git+https://github.com/yourusername/easy_mcp_rag.git easy_mcp_rag --data-dir ./documents

Install with UV

# Install from GitHub
uv pip install git+https://github.com/yourusername/easy_mcp_rag.git

# Or clone and install locally
git clone https://github.com/yourusername/easy_mcp_rag.git
cd easy_mcp_rag
uv pip install -e .

📋 Prerequisites

Start Qdrant (using Docker):

docker run -p 6333:6333 qdrant/qdrant

Prepare your documents:

documents/
├── legal_docs/
│   ├── contract.pdf
│   └── terms.docx
├── research/
│   ├── paper1.pdf
│   └── notes.txt
└── data/
    └── analysis.csv

💻 Usage

Basic Usage (stdio)

# With UVX
uvx --from git+https://github.com/yourusername/easy_mcp_rag.git easy_mcp_rag --data-dir ./documents

# With UV
uv run easy_mcp_rag --data-dir ./documents

# After installation
easy_mcp_rag --data-dir ./documents

HTTP Mode

easy_mcp_rag --data-dir ./documents --transport http --http-port 8000

GPU Acceleration

# Auto-detect GPU
easy_mcp_rag --data-dir ./documents --device auto

# Force CUDA (NVIDIA GPU)
easy_mcp_rag --data-dir ./documents --device cuda

# Force MPS (Apple Silicon)
easy_mcp_rag --data-dir ./documents --device mps

# Force CPU
easy_mcp_rag --data-dir ./documents --device cpu

Advanced Configuration

easy_mcp_rag \
  --data-dir ./documents \
  --qdrant-host localhost \
  --qdrant-port 6333 \
  --device cuda \
  --embedding-model all-mpnet-base-v2 \
  --chunk-size 1024 \
  --chunk-overlap 100 \
  --top-k 10 \
  --batch-size 64 \
  --verbose \
  --force-reindex

🔧 Configuration Options

| Flag | Description | Default | |------|-------------|---------| | --data-dir | Directory with document subdirectories | Required | | --qdrant-host | Qdrant server host | localhost | | --qdrant-port | Qdrant server port | 6333 | | --device | Device: auto, cpu, cuda, mps | auto | | --transport | Transport type: stdio, http | stdio | | --http-host | HTTP server host | 0.0.0.0 | | --http-port | HTTP server port | 8000 | | --embedding-model | Sentence transformer model | all-MiniLM-L6-v2 | | --chunk-size | Text chunk size (chars) | 512 | | --chunk-overlap | Chunk overlap (chars) | 50 | | --top-k | Results per search | 5 | | --batch-size | Embedding batch size | 32 | | --verbose | Enable verbose logging | False | | --log-level | Log level | INFO | | --force-reindex | Force reindex all docs | False |

🎯 MCP Client Configuration

Claude Desktop / Cline / Other MCP Clients

Add to your MCP client config:

{
  "mcpServers": {
    "rag-server": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/yourusername/easy_mcp_rag.git",
        "easy_mcp_rag",
        "--data-dir",
        "/path/to/your/documents",
        "--device",
        "auto",
        "--verbose"
      ]
    }
  }
}

With HTTP Transport

{
  "mcpServers": {
    "rag-server": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/yourusername/easy_mcp_rag.git",
        "easy_mcp_rag",
        "--data-dir",
        "/path/to/your/documents",
        "--transport",
        "http",
        "--http-port",
        "8000"
      ]
    }
  }
}

🛠️ How It Works

Scan - Discovers all subdirectories in your data directory
Load - Extracts text from all supported file types
Chunk - Splits documents into overlapping chunks
Embed - Generates vector embeddings (CPU or GPU)
Index - Stores in Qdrant (one collection per subdirectory)
Serve - Creates MCP tools for each collection

Example

documents/
├── legal_docs/      → Creates "legal_docs_search" tool
├── research/        → Creates "research_search" tool
└── data/            → Creates "data_search" tool

📄 Supported File Types

| Category | Extensions | |----------|-----------| | Text | .txt, .md, .py, .js, .json, .xml, .html, .css | | PDF | .pdf | | Word | .docx, .doc | | Spreadsheet | .csv, .xlsx, .xls |

🎨 Embedding Models

Choose based on your needs:

| Model | Dimensions | Speed | Quality | Use Case | |-------|-----------|-------|---------|----------| | all-MiniLM-L6-v2 | 384 | ⚡⚡⚡ | Good | Default, fast | | all-MiniLM-L12-v2 | 384 | ⚡⚡ | Better | Balanced | | all-mpnet-base-v2 | 768 | ⚡ | Best | Quality |

🐛 Troubleshooting

Qdrant Connection Failed

# Check if Qdrant is running
curl http://localhost:6333

# Start Qdrant
docker run -p 6333:6333 qdrant/qdrant

GPU Not Detected

# Check PyTorch GPU support
python -c "import torch; print(torch.cuda.is_available())"

# Install with GPU support
uv pip install -e ".[gpu]"

Out of Memory

# Use smaller model
--embedding-model all-MiniLM-L6-v2

# Reduce batch size
--batch-size 16

# Use CPU
--device cpu

📊 Logging

Enable verbose logging to see detailed information:

easy_mcp_rag --data-dir ./documents --verbose

Output includes:

✅ Tool access events
🔍 Query details
📈 Result counts
🎯 Relevance scores
📁 Source files

Example: `` 2024-01-20 10:30:15 - easy_mcp_rag.server - INFO - Tool accessed: legal_docs_search 2024-01-20 10:30:15 - easy_mcp_rag.server - INFO - Query: contract terms 2024-01-20 10:30:15 - easy_mcp_rag.server - INFO - Results returned: 5 2024-01-20 10:30:15 - easy_mcp_rag.server - DEBUG - Result 1: score=0.8542 ``

🔐 Security Notes

HTTP mode exposes the server on the network
Use --http-host 127.0.0.1 for local-only access
Consider authentication for production deployments

📝 Development

# Clone repository
git clone https://github.com/yourusername/easy_mcp_rag.git
cd easy_mcp_rag

# Install with dev dependencies
uv pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/

# Lint
ruff src/

🤝 Contributing

Contributions welcome! Please:

Fork the repository
Create a feature branch
Make your changes
Submit a pull request

📜 License

MIT License - see LICENSE file

🙏 Credits

Built with:

MCP - Model Context Protocol
Qdrant - Vector database
Sentence Transformers - Embeddings
UV - Package manager

Easy MCP RAG