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Use RushDB with AI Agents

RushDB gives agents a structured data layer, a traversable graph, and persistent memory. Choose the shortest setup that matches your agent.

Fastest Setup: Give the Agent the Guide​

For an MCP-capable agent, send:

Fetch https://rushdb.com/agent-setup and follow the instructions exactly.

The machine-readable setup guide walks the agent through MCP connection, schema discovery, memory labels, nested record linking, recall patterns, and semantic search.

Coding Assistant: MCP + Skills + Memory​

For Claude Desktop, Cursor, VS Code Copilot, OpenClaw, or another local coding agent:

  1. Connect the local MCP server.
  2. Install RushDB Agent Skills.
  3. Start a new agent session.
  4. Send:
Set up RushDB as my persistent memory layer.

The agent calls getOntologyMarkdown, creates a SESSION, and validates recall. For the full bootstrap prompt and recommended labels, follow the Agent Memory Quickstart.

Custom Agent Harness​

For an application-controlled agent, choose the interface based on where orchestration lives:

InterfaceUse it when
MCP toolsYour framework already supports MCP tool discovery and invocation
TypeScript SDKYour harness runs in Node.js, the browser, or an edge-compatible runtime
Python SDKYour harness runs in Python
REST APIYou need language-neutral HTTP integration

Connect with an SDK or REST →

At the start of each agent session:

  1. Call getOntologyMarkdown to discover the live schema.
  2. Recall the latest SESSION and relevant DECISION, TASK, or PREFERENCE records.
  3. Create a new SESSION.

Before the session ends:

  1. Store decisions, tasks, observations, and artifacts.
  2. Link them to the session through nested JSON or relationships.
  3. Confirm the stored summary.

Verify​

Ask your agent:

Search RushDB for SESSION records. Show the most recent one and summarize any linked decisions or tasks.

If you have not bootstrapped memory yet, use the Agent Memory Quickstart first.

Next Steps​