qdrant/mcp-server-qdrant

4.0

mcp-server-qdrant is hosted online, so all tools can be tested directly either in theInspector tabor in theOnline Client.

If you are the rightful owner of mcp-server-qdrant and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

The mcp-server-qdrant is a Model Context Protocol server designed to integrate with the Qdrant vector search engine, providing a semantic memory layer for storing and retrieving information.

Try mcp-server-qdrant with chat:

Tools

Functions exposed to the LLM to take actions

qdrant-find

Look up memories in Qdrant. Use this tool when you need to:

Find memories by their content
Access memories for further analysis
Get some personal information about the user

qdrant-store

Keep the memory for later use, when you are asked to remember something.

Prompts

Interactive templates invoked by user choice

No prompts

Resources

Contextual data attached and managed by the client

No resources

Author

qdrant

Claim Ownership

Verify you have write access to the repository

Version

v0.8.0

Repository

https://github.com/qdrant/mcp-server-qdrant

Homepage

https://qdrant.tech

GitHub Stars

888

License

Apache License 2.0

Last publish date

2025-06-27

Last update date

2025-08-30

Server configs

via uvx in claude desktop

{
  "qdrant": {
    "command": "uvx",
    "args": ["mcp-server-qdrant"],
    "env": {
      "QDRANT_URL": "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333",
      "QDRANT_API_KEY": "your_api_key",
      "COLLECTION_NAME": "your-collection-name",
      "EMBEDDING_MODEL": "sentence-transformers/all-MiniLM-L6-v2"
    }
  }
}

via uvx in vs code

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "qdrantUrl",
        "description": "Qdrant URL"
      },
      {
        "type": "promptString",
        "id": "qdrantApiKey",
        "description": "Qdrant API Key",
        "password": true
      },
      {
        "type": "promptString",
        "id": "collectionName",
        "description": "Collection Name"
      }
    ],
    "servers": {
      "qdrant": {
        "command": "uvx",
        "args": ["mcp-server-qdrant"],
        "env": {
          "QDRANT_URL": "${input:qdrantUrl}",
          "QDRANT_API_KEY": "${input:qdrantApiKey}",
          "COLLECTION_NAME": "${input:collectionName}"
        }
      }
    }
  }
}

in vs code

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "qdrantUrl",
        "description": "Qdrant URL"
      },
      {
        "type": "promptString",
        "id": "qdrantApiKey",
        "description": "Qdrant API Key",
        "password": true
      },
      {
        "type": "promptString",
        "id": "collectionName",
        "description": "Collection Name"
      }
    ],
    "servers": {
      "qdrant": {
        "command": "docker",
        "args": [
          "run",
          "-p", "8000:8000",
          "-i",
          "--rm",
          "-e", "QDRANT_URL",
          "-e", "QDRANT_API_KEY",
          "-e", "COLLECTION_NAME",
          "mcp-server-qdrant"
        ],
        "env": {
          "QDRANT_URL": "${input:qdrantUrl}",
          "QDRANT_API_KEY": "${input:qdrantApiKey}",
          "COLLECTION_NAME": "${input:collectionName}"
        }
      }
    }
  }
}

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