MemoCat — Shared AI Memory

MemoCat — Shared AI Memory runs locally from a Python package published to PyPI: memocat-mcp version 0.4.3. It speaks MCP over stdio, so the client starts it as a program and talks to it through standard input and output. It needs Python; clients usually start it with uvx (from uv) or after pip install — the usual command is uvx memocat-mcp. It reads these environment variables: MONTYCAT_URI (secret) and MONTYCAT_TLS; set them in the client's configuration for this server.

MemoCat — Shared AI Memory runs locally from a container image in an OCI registry such as Docker Hub or GitHub Container Registry: docker.io/montygovernance/memocat-mcp:0.4.3. It speaks MCP over stdio, so the client starts it as a program and talks to it through standard input and output. It needs Docker or another OCI container runtime; started with docker run — the usual command is docker run -i --rm -e MONTYCAT_URI -e MONTYCAT_TLS docker.io/montygovernance/memocat-mcp:0.4.3. It reads these environment variables: MONTYCAT_URI (secret) and MONTYCAT_TLS; set them in the client's configuration for this server.

In the mcpServers JSON format that many desktop and editor MCP clients read, the entry looks like this (placeholders in angle brackets):

{
  "mcpServers": {
    "memocat-mcp": {
      "command": "uvx",
      "args": [
        "memocat-mcp"
      ],
      "env": {
        "MONTYCAT_URI": "<secret>",
        "MONTYCAT_TLS": "<value>"
      }
    }
  }
}

Derived from the registry entry, not tested here. What the server does, and on what terms, is set by its publisher; check its repository or website before giving it access to your accounts or files. How to add an MCP server to an assistant · Before you connect