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Qdrant

qdrant/mcp-server-qdrantOfficial

The Qdrant MCP server provides semantic memory capabilities by integrating the Qdrant vector search engine with language models through the Model Context Protocol. It offers two main tools: `qdrant-store` for persisting information with optional metadata into Qdrant collections, and `qdrant-find` for retrieving semantically relevant information through vector search queries. The server solves the problem of enabling LLMs to maintain and access persistent, semantically-indexed memory across conversations by acting as a memory layer on top of a vector database.

GitHub stars
1.4K
tools
2
last updated
Mar 10, 2026

Tools

2 tools

Public tool metadata for what this MCP can expose to an agent.

qdrant-storeStore some information in the Qdrant database

Store some information in the Qdrant database

No parameter schema in public metadata yet.

qdrant-findRetrieve relevant information from the Qdrant database

Retrieve relevant information from the Qdrant database

No parameter schema in public metadata yet.

Sponsors

Readme

mcp-server-qdrant: A Qdrant MCP server

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The 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.

Overview

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.

Components

Tools


View the full README on GitHub

Details

Repository
github.com/qdrant/mcp-server-qdrant
Category
AI & LLM Tools

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