Skip to main content
Kaino.dev
Discover
Evals
News
Academics
Insights
Kaino.dev

Discover, evaluate, and compare AI tools, models, and agents.

Explore

  • Discover
  • Evaluations
  • News
  • Academics
  • Insights

Community

  • Twitter
  • YouTube
  • Instagram
Privacy PolicyTerms of Service

© 2026 Kaino.dev. All rights reserved.

Version 1.1.0
Qdrant MCP Server · Discover · Kaino
Discover/MCP'S/Qdrant MCP Server
Qdrant MCP Server logo

MCP'S

Qdrant MCP Server

by Qdrant

mcpsource:qdrant.techqdrantvector-searchsemantic-memorycode-search
Visit WebsiteDocumentationGitHub

Overview

Official Qdrant MCP server for storing and retrieving semantic memories or code-search context using Qdrant vector search collections.

Details

Qdrant MCP Server is described by Qdrant sources as the official Qdrant MCP server for storing and retrieving semantic memories or code-search context using Qdrant vector search collections. The supplied official website, documentation, and GitHub repository all identify the project as Qdrant MCP Server and describe the same purpose: connecting MCP workflows with Qdrant-backed vector search collections for memory and code-search context retrieval.

When to Use

Use when an MCP-compatible workflow needs to store and retrieve semantic memories with Qdrant vector search collections. Use when an MCP-compatible coding or assistant workflow needs code-search context retrieved from Qdrant collections.

Getting Started

  1. Review the official Qdrant documentation at https://qdrant.tech/documentation/.
  2. Inspect the official GitHub repository at https://github.com/qdrant/mcp-server-qdrant.
  3. Use the official Qdrant website at https://qdrant.tech/ as the provider entry point for the project.

Key Features

  • •Official Qdrant MCP server.
  • •Stores and retrieves semantic memories.
  • •Supports code-search context retrieval.
  • •Uses Qdrant vector search collections.

Capabilities

  • •MCP server
  • •semantic memory storage and retrieval
  • •code-search context retrieval
  • •Qdrant vector search collection integration

Last updated Jun 10, 2026