YantrikDB MCP Server

Cognitive memory for AI agents. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible client.

Website: yantrikdb.com · Docs: yantrikdb.com/guides/mcp · GitHub: yantrikos/yantrikdb-mcp

Install

# Default — uses the engine's bundled 64-dim embedder. ~10 MB install,
# ~80 ms cold start, no native ML deps.
pip install yantrikdb-mcp

# Optional: higher-quality 384-dim ONNX MiniLM-L6-v2 embedder (~150 MB install).
# Auto-used when an existing pre-v0.6 database is detected.
pip install 'yantrikdb-mcp[onnx]'

Upgrading from v0.5.x? Your existing database stays at 384 dim — install the [onnx] extra to keep using it transparently. New installs default to the lean bundled embedder. v0.7.0+ pins the engine migration fix automatically. See Embedder backends below.

Configure

The MCP server has three deployment modes. Pick the one that fits your setup.

Mode 1 — Local (default, recommended for single user)

The MCP server runs the engine in-process with a local SQLite database. Fast, private, zero dependencies.

{
  "mcpServers": {
    "yantrikdb": {
      "command": "yantrikdb-mcp"
    }
  }
}

That's it. The agent auto-recalls context, auto-remembers decisions, and auto-detects contradictions — no prompting needed.

Mode 2 — HTTP Cluster (recommended for shared/multi-machine setups)

Forward all tool calls to a YantrikDB HTTP cluster instead of using an embedded engine. The MCP server is a thin stateless client — all memories live on the cluster, accessible from any machine.

Benefits: shared memory across machines, high availability, no local embedder download, no local database.

{
  "mcpServers": {
    "yantrikdb": {
      "command": "yantrikdb-mcp",
      "env": {
        "YANTRIKDB_SERVER_URL": "http://node1:7438,http://node2:7438",
        "YANTRIKDB_TOKEN": "ydb_your_database_token"
      }
    }
  }
}

• Comma-separate multiple nodes for Raft cluster auto-discovery
• Automatic leader-following on failover
• 15s request timeout
• Get the token from the cluster: yantrikdb token create --db your_database

Mode 3 — SSE Server (legacy, single remote instance)

Run the MCP server itself as a long-running SSE server with its own embedded database. Clients connect via HTTP streaming.

# Generate a secure API key
export YANTRIKDB_API_KEY=$(python -c "import secrets; print(secrets.token_urlsafe(32))")

# Start SSE server
yantrikdb-mcp --transport sse --port 8420

{
  "mcpServers": {
    "yantrikdb": {
      "type": "sse",
      "url": "http://your-server:8420/sse",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Supports sse and streamable-http transports. Note: SSE connections can drop on idle — Mode 2 (HTTP Cluster) is more reliable for shared deployments.

Environment Variables

... View full README on GitHub