YantrikDB MCP Server

YantrikDB — Cognitive memory for AI agents. Persistent semantic recall, knowledge graph, contradiction detection, and procedural learning. Ships as embeddable engine, network database, or MCP server.

Works with Claude Code, Cursor, Windsurf, Hermes Agent, Prime Agent, and any MCP-compatible client. Ships a portable Agent Skills skill — skills/persistent-memory — that teaches any compliant harness the memory golden path.

Website: yantrikdb.com · Docs: yantrikdb.com/guides/mcp · GitHub: yantrikos/yantrikdb-mcp · Paper: Skill as Memory, Not Document

Every value on screen is the server's own answer over MCP — driver: docs/demo/demo.py, recorded with docs/demo/demo.tape.

At a glance

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 ser

... View full README on GitHub