This is a weekend project to create a simple RAG application that stores embeddings of text documents using Qdrant, and a MCP server to query this Vector Database, and a MCP client using Claude to interact.
- Jupyter notebook
idx_qdrant.ipynb
has the Python code to index documents into Qdrant. - Copy
.env.example
to.env
and fill in the values. - Run the MCP server using
./run_server.sh
. - In another terminal, run the MCP client using
./run_client.sh
.