Open source · MIT · self-hosted

Git for MongoDB,
built for AI agents

Give each agent its own database branch. Test changes, revisit earlier states, and review what to merge.

No login. Sample data in your own temporary session.

orders / order-1

Illustration
mainagent

main

price
49

Unchanged

planner

price
49

Same baseline

Branch pointprice: 49

Start from the same data.

Give the planner agent its own branch of orders. Both start with the same document.

How it works
Install the CLI with npm
npm install -g argonctl@2.1.1

Installs the argon CLI. Requires Node.js 18 or newer.

Published release: v2.1.1

Read the release notes

Use the tools you already have

An agent branch checks out as a real MongoDB database. Keep your usual driver; use Argon to manage its history and review its work.

Connect an agent

Give Claude Code or Cursor database tools through MCP.

Set up MCP

Build in Python

Run the review workflow with the SDK, then add it to your agent.

Use the Python SDK

Use your own stack

Create sandboxes and inspect changes from any HTTP client.

Call the REST API

Try the idea.
Then use your data.

In the live demo

Compare two agents’ proposals on sample orders. Inspect a conflict and undo a rejected change in a temporary session.

In your deployment

Connect your own MongoDB replica set. Agents write to separate branch databases; applying a reviewed merge changes the target.

Time travel depends on retained history and complete capture. Physical checkout takes time and storage that depend on the dataset. Read the operating boundaries.

Check the work

The two-agent example checks the starting data, a real conflict, the accepted change, and the restored result. Run it locally without an LLM key.

Historical metadata measurements

0.86 ms branch p50 and 479 B per metadata branch, measured with engine 8bf0f1e on a 50k-entry project. These historical numbers exclude physical checkout, sandbox readiness, and MongoDB storage. The benchmark report includes end-to-end measurements and their scope.

Review your first change

Start with a sample order. See what the agent changed.

Try live demo