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Project description
better-qdrant-mcp
A MCP server implemented with fastmcp, OpenAI embeddings, and qdrant-client. It provides three tools equivalent to the Node.js version:
- memory-store
- memory-search
- memory-debug
Requirements
- Python 3.12+
- Qdrant reachable via HTTP
Install deps (using uv or pip)
# using uv (recommended)
uv sync
# or with pip
pip install -e .
Environment variables
- QDRANT_URL (default: http://localhost:6333)
- QDRANT_API_KEY (optional)
- COLLECTION_NAME (optional default collection)
- OPENAPI_API_KEY or OPENAI_API_KEY (required)
- OPENAI_BASE_URL (optional)
- OPENAI_EMBEDDING_MODEL (default: text-embedding-3-small)
Run (stdio)
uvx better-qdrant-mcp
You can still run it via Python directly if you prefer:
python -m better_qdrant_mcp
Configure in MCP clients as a stdio server. Example (cursor-like):
{
"mcpServers": {
"qdrant-mcp-python": {
"type": "stdio",
"command": "uvx",
"args": ["better-qdrant-mcp"],
"env": {
"QDRANT_URL": "http://localhost:6333",
"COLLECTION_NAME": "long_term_memory"
}
}
}
}
Tools
- memory-store(information, metadata?: dict, collection_name?: str) -> str
- memory-search(query, limit?: int=5, collection_name?: str) -> str
- memory-debug(collection_name?: str) -> str
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