Hivemind

io.github.monochrome-muncher/hivemind · v2.26.0

Shared long-term memory for a team's AI agents. What one agent learns, the others can find.

Website Source code Set it up

Connect Runs on your machine

Terminal

claude mcp add hivemind -e HIVEMIND_DATABASE_URL=<HIVEMIND_DATABASE_URL> -e HIVEMIND_EMBEDDING_ENDPOINT=<HIVEMIND_EMBEDDING_ENDPOINT> -e HIVEMIND_EMBEDDING_MODEL=<HIVEMIND_EMBEDDING_MODEL> -e HIVEMIND_EMBEDDING_DIM=<HIVEMIND_EMBEDDING_DIM> -e HIVEMIND_EMBEDDING_API_KEY=<HIVEMIND_EMBEDDING_API_KEY> -- docker run -i --rm ghcr.io/monochrome-muncher/hivemind:v2.26.0

claude_desktop_config.json

{
  "mcpServers": {
    "hivemind": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/monochrome-muncher/hivemind:v2.26.0"
      ],
      "env": {
        "HIVEMIND_DATABASE_URL": "<HIVEMIND_DATABASE_URL>",
        "HIVEMIND_EMBEDDING_ENDPOINT": "<HIVEMIND_EMBEDDING_ENDPOINT>",
        "HIVEMIND_EMBEDDING_MODEL": "<HIVEMIND_EMBEDDING_MODEL>",
        "HIVEMIND_EMBEDDING_DIM": "<HIVEMIND_EMBEDDING_DIM>",
        "HIVEMIND_EMBEDDING_API_KEY": "<HIVEMIND_EMBEDDING_API_KEY>"
      }
    }
  }
}

~/.cursor/mcp.json

{
  "mcpServers": {
    "hivemind": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/monochrome-muncher/hivemind:v2.26.0"
      ],
      "env": {
        "HIVEMIND_DATABASE_URL": "<HIVEMIND_DATABASE_URL>",
        "HIVEMIND_EMBEDDING_ENDPOINT": "<HIVEMIND_EMBEDDING_ENDPOINT>",
        "HIVEMIND_EMBEDDING_MODEL": "<HIVEMIND_EMBEDDING_MODEL>",
        "HIVEMIND_EMBEDDING_DIM": "<HIVEMIND_EMBEDDING_DIM>",
        "HIVEMIND_EMBEDDING_API_KEY": "<HIVEMIND_EMBEDDING_API_KEY>"
      }
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "hivemind": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/monochrome-muncher/hivemind:v2.26.0"
      ],
      "env": {
        "HIVEMIND_DATABASE_URL": "<HIVEMIND_DATABASE_URL>",
        "HIVEMIND_EMBEDDING_ENDPOINT": "<HIVEMIND_EMBEDDING_ENDPOINT>",
        "HIVEMIND_EMBEDDING_MODEL": "<HIVEMIND_EMBEDDING_MODEL>",
        "HIVEMIND_EMBEDDING_DIM": "<HIVEMIND_EMBEDDING_DIM>",
        "HIVEMIND_EMBEDDING_API_KEY": "<HIVEMIND_EMBEDDING_API_KEY>"
      }
    }
  }
}

Replace the values in angle brackets with your own. Keys stay on your machine; we never see them.

Tools

This server runs locally, so its tools are listed by your MCP client once it starts.

Environment variables

Name	Description
`HIVEMIND_DATABASE_URL` Required, secret	Postgres 16+ with pgvector 0.8+, for example postgresql://user:password@host:5432/hivemind. Migrations run when the container starts.
`HIVEMIND_EMBEDDING_ENDPOINT` Required	An OpenAI-compatible embeddings endpoint, for example a local vLLM at http://host.docker.internal:8001/v1.
`HIVEMIND_EMBEDDING_MODEL` Optional	The embedding model name the endpoint serves.
`HIVEMIND_EMBEDDING_DIM` Optional	Vector width; must match the model and stay the same for the life of the database (at most 2000).
`HIVEMIND_EMBEDDING_API_KEY` Optional, secret	API key for the embedding endpoint, if it needs one.

Details

Package	`ghcr.io/monochrome-muncher/hivemind:v2.26.0` (OCI, streamable-http)
First published	13 Nov 2026
Last updated	13 Nov 2026
Registry name	`io.github.monochrome-muncher/hivemind`

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Live status

Local install

Installed and run on your own machine, so there is no public endpoint to check.

Pair it with live search

Agents that use Hivemind often also need current facts. NestDaddy MCP gives your AI today's internet: web search, real-time breaking news and full page reading in one connector.

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