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Steps to run

  1. Install Python Libraries:
pip install -r requirements.txt
  1. Create the .env File:
# Add any API keys or secrets here later
FIRECRAWL_API_KEY = ""
OPENAI_API_KEY = ""
  1. Launch the Vector Database (Qdrant):
docker run -p 6333:6333 -p 6334:6334 -v $(pwd)/qdrant_storage:/qdrant/storage qdrant/qdrant
  1. Run the server:
python3 mcp_server.py
  1. To inspect execute:
pnpx @modelcontextprotocol/inspector python3 mcp_server.py

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A fully functional and intelligent application capable of fielding complex queries by dynamically sourcing the best possible context for a truly accurate answer leveraging agentic RAG and MCP.

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