MCP Servers · Memory
qdrant/mcp-server-qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
Our verdict
We have not reviewed qdrant/mcp-server-qdrant yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About qdrant/mcp-server-qdrant
An official Model Context Protocol (MCP) server for Qdrant vector database. It enables AI agents to perform semantic search, store and retrieve vector embeddings, and manage collections through the standardized MCP interface. Written in Python, it provides a direct bridge between MCP-compatible clients and Qdrant's vector storage capabilities.
Best for
Developers building MCP-compatible AI agents that need vector search and memory via Qdrant
Use cases
- Building AI agents that need long-term memory via vector embeddings
- Enabling semantic search over documents or knowledge bases from an MCP client
- Integrating Qdrant vector storage into MCP-based agent workflows
Notes
1,420 stars on GitHub. Last updated 2026-05-20. Licensed Apache-2.0.
Pros
- Official implementation maintained by Qdrant
- Leverages the MCP standard for interoperability with many AI clients
- Python-based, easy to extend or embed in existing Python projects
Cons
- Requires a running Qdrant instance (local or cloud) to function
- Limited to the MCP protocol; not a general-purpose Qdrant client
- Setup and configuration may be non-trivial for beginners
Key facts
What we have checked
Not checked yet. Dated facts such as prices, releases and repository activity appear here once we have confirmed them from a source.
How to use
How to set it up
As the listing publishes it. We have not run this install.
Install
npx @smithery/cli install mcp-server-qdrant --client claudeTools exposed
informationmetadatacollection_nameQDRANT_URLQDRANT_API_KEYCOLLECTION_NAMEQDRANT_LOCAL_PATHEMBEDDING_PROVIDEREMBEDDING_MODELTOOL_STORE_DESCRIPTIONTOOL_FIND_DESCRIPTIONQDRANT_SEARCH_LIMITQDRANT_READ_ONLYFASTMCP_LOG_LEVELFASTMCP_SERVER_DEBUGFASTMCP_SERVER_HOSTFASTMCP_SERVER_PORTFASTMCP_SERVER_ON_DUPLICATE_RESOURCESFASTMCP_SERVER_ON_DUPLICATE_TOOLSFASTMCP_SERVER_ON_DUPLICATE_PROMPTS
Clients the listing names (not checked here)
Claude Desktop, Claude Code, Cursor, Windsurf, VS Code
Install
Add qdrant/mcp-server-qdrant to your client
No install recipe yet. We write one for Claude Code, Claude Desktop, Cursor, VS Code, Codex and ChatGPT when the server is in the official MCP registry with a package or remote address we can use.
Until then, follow the project's own README, or the setup the listing publishes under How to set it up.
Works with
What qdrant/mcp-server-qdrant connects to
1 product, each with how we know and when we checked.
| Works with | Type | How we know | Checked |
|---|---|---|---|
| Qdrant | Product | Its repo belongs to the product's GitHub organisationGitHub org qdrant | GitHub |
Health and security
Is qdrant/mcp-server-qdrant looked after, and what do its setup files show
Security check static checks
97 out of 100
- Low The documented install uses @smithery/cli, whose published metadata points at github.com/smithery-ai/cli, not this repository. Check it is the right package before installing.
- Note No published npm or PyPI package of this repository was found, so package advisories were not checked.
- Note The lab has not recorded this server's tool list yet, so tool permissions were not checked.
Sources
Where this comes from
No sources recorded yet. Each source we check is listed here with the date we checked it.
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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