RAG_MCP
A RAG-ready MCP server for semantic PDF search with OCR, FAISS, and transformers—plug into any MCP client and retrieve intelligent answers within your MCP client.
Step 1: Create virtual env and install requirements
curl -LsSf https://astral.sh/uv/install.sh | sh
uv init rag_mcp
cd rag_mcp
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
brew install tesseract
Step 2a: Add config to the Claude MCP client
code ~/Library/Application\ Support/Claude/claude_desktop_config.json
...
{
"mcpServers": {
"rag": {
"command": "/Users/XXX/.local/bin/uv",
"args": [
"--directory",
"/Users/XXX/Documents/RAG_MCP",
"run",
"rag.py"
]
}
}
}
Step 2b: Add config to the Cursor MCP client
code ~/.cursor/mcp.json
...
{
"mcpServers": {
"rag": {
"command": "/Users/XXX/Documents/RAG_MCP/start.sh",
"args": []
}
}
}
Step 5: Make MCP server executable
chmod +x start.sh
chmod +x rag.py
Step 6: Run MCP server (Claude Desktop)
uv run rag.py
Step 7: Run MCP client and query
Parse the pdfs and tell me about 18 Church St. and what significance it has.