by qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
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git clone https://github.com/qdrant/mcp-server-qdrantThe Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
An official Model Context Protocol server for keeping and retrieving memories in the Qdrant vector search engine. It acts as a semantic memory layer on top of the Qdrant database.
qdrant-store
information (string): Information to storemetadata (JSON): Optional metadata to storecollection_name (string): Name of the collection to store the information in. This field is required if there are no default collection name.
If there is a default collection name, this field is not enabled.qdrant-find
query (string): Query to use for searchingcollection_name (string): Name of the collection to store the information in. This field is required if there are no default collection name.
If there is a default collection name, this field is not enabled.No comments yet. Be the first to share your thoughts!
The configuration of the server is done using environment variables:
| Name | Description | Default Value |
|--------------------------|---------------------------------------------------------------------|-------------------------------------------------------------------|
| QDRANT_URL | URL of the Qdrant server | None |
| QDRANT_API_KEY | API key for the Qdrant server | None |
| COLLECTION_NAME | Name of the default collection to use. | None |
| QDRANT_LOCAL_PATH | Path to the local Qdrant database (alternative to QDRANT_URL) | None |
| EMBEDDING_PROVIDER | Embedding provider to use (currently only "fas...