mcp-server-qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
No outside reports on file
This tool gives AI direct control over a vector database, so only connect it to a Qdrant instance containing data you trust the AI to access and modify.
Based on public adoption and transparency signals as of Oct 22, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachConnects to outside service APINOTED
- CredentialsNo API token requiredLOW
- Package sourceGitHub (qdrant/mcp-server-qdrant)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
No npm or PyPI package is listed. Install from source: github.com/qdrant/mcp-server-qdrant ↗
Everything known
We found nothing about this project in the sources we read (last checked 2026-10-30). That does not mean it has no problems.
0 incidents · 0 advisories · 0 news articles · 9 community threads · checked 2026-10-30
Popularity grade: C (from public signals such as stars and downloads, not a code review). Graded 2026-10-22.
Showing all 9Showing 9 community threads of 9
- CommunityDoes mcp-server-qdrant have a qdrant-delete tool, and is it hidden in read_only mode?
- CommunityHow do I connect mcp-server-qdrant to a local Qdrant database by folder path?
- CommunityHow to fix timeout when storing Japanese text with mcp-server-qdrant on Windows?
- CommunityHow to use custom or local embedding models (Ollama, vLLM) with mcp-server-qdrant?
- CommunityHow to use mcp-server-qdrant with existing Qdrant collections when vector name doesn't match?
- CommunityIs there a way to edit or delete a record in mcp-server-qdrant?
- Communitymcp-server-qdrant 400: "Vector with name fast-bge-small-en-v1.5 is not configured in this collection"
- Communitymcp-server-qdrant ignores FASTMCP_HOST/FASTMCP_PORT — correct env vars?
- Communityqdrant-find fails with 'document': what payload structure does the MCP server expect?
Sources we read: OSV, GitHub Advisory Database, CISA Known Exploited Vulnerabilities, 44 security news feeds and our incident library. Last checked 2026-10-30.
About MCP Server Qdrant
This tool connects Claude and other AI models to Qdrant, a vector database (a system that stores and searches data based on similarity). It lets AI systems store, search, and manage embeddings—numerical representations of text or images—for tasks like semantic search and recommendation systems.
Who it’s for
Developers building AI applications that need to store or search through large amounts of text or image data using vector similarity. Teams using Qdrant for vector storage who want to integrate it with Claude or other MCP-compatible AI tools.
Alternatives
- Pinecone MCP server: Another vector database with MCP support; may offer managed infrastructure.
- Weaviate integrations: Alternative vector database with AI integration options.
- Custom MCP tools: Build your own MCP server with fine-grained access controls instead of using official connectors.
Setup
Check these steps against the project’s own instructions before running anything.
Follow the setup steps in the project’s official README: https://github.com/qdrant/mcp-server-qdrant (opens external site)
Why this grade
Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 1.6k
- Listing last refreshed
- 2026-10-29
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Risks to watch for
- Database access: This connector can read, write, and delete data stored in your Qdrant instance. If Qdrant holds sensitive information, the AI gains direct access to it.
- No built-in filtering: The tool may not limit which collections or data the AI can reach. An attacker controlling the AI could browse or modify all stored embeddings.
- Prompt injection: Malicious text fed into the AI could trick it into running unintended vector searches or database commands.
- Network exposure: If Qdrant is exposed to the internet, this connector makes it reachable by any process running the AI system.
- Data leakage: Sensitive embeddings or metadata stored in Qdrant could be extracted through the AI and leaked in responses.
How to lower the risk
Least-privilege permissions
- Create a Qdrant user account with read-only or minimal write access if possible.
- Limit the connector to specific collections instead of full database access.
Network isolation
- Run Qdrant behind a firewall or private network, never exposed to the internet.
- Use local connections (localhost) if the AI system runs on the same machine.
Monitoring
- Log all vector search and database modification queries the AI makes.
- Review logs regularly for unexpected data access patterns.
Red flags to watch for
- Unusual database queries or access to unexpected collections.
- Unexpected increases in data retrieval or modification volume.
- Errors or crashes that suggest the AI is probing database boundaries.
Questions
How do I install MCP Server Qdrant?
MCP Server Qdrant does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/qdrant/mcp-server-qdrant.
Are there security reports about MCP Server Qdrant?
No reports found for this package in our research (last checked 2026-10-30). MCP Server Qdrant currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include database access, no built-in filtering, prompt injection.
Is MCP Server Qdrant actively maintained?
MCP Server Qdrant has 1.6k GitHub stars. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/qdrant/mcp-server-qdrant before pinning it in production.
What are alternatives to MCP Server Qdrant?
Notable alternatives to MCP Server Qdrant include Pinecone MCP server (Another vector database with MCP support), Weaviate integrations (Alternative vector database with AI integration options), Custom MCP tools (Build your own MCP server with fine-grained access controls instead of using official connectors). You can also compare MCP Server Qdrant side by side with other MCP servers in the Related tools section on this page.
Key facts
- Type
- App connector
- Publisher
- qdrant
- Source code
- github.com/qdrant/mcp-server-qdrant
- Est. context load
- ~1.4k tokens / turn (~8 tool schemas, 0.68% of 200k context)
- Popularity
- 1.6k GitHub stars
- Last updated
- 2026-10-29
- Last graded
- 2026-10-22
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