For scripts and Python agent workers
Python
Use the Python SDK to report a run lifecycle and meaningful steps. Add checkpoints and guarded actions when you want compatible human control.
See setup instructions →INTEGRATIONS / BRING YOUR OWN AGENTS
Choose your agent supervision integration: Python, Node.js, or the HTTP contract. Keep your runtime and add meaningful activity, outcome, and control reporting.

For scripts and Python agent workers
Use the Python SDK to report a run lifecycle and meaningful steps. Add checkpoints and guarded actions when you want compatible human control.
See setup instructions →For JavaScript workers and services
Use the Node.js SDK from the process that owns the work. Report outcomes and usage where available, then inspect them in the workspace.
See setup instructions →For other runtimes and workflow tools
Connect software that can make outbound HTTPS requests. Implement the documented reporting contract and use an agent-scoped credential.
See setup instructions →A SMALL, DELIBERATE INTEGRATION
Local · cloud · scheduled
Activity · incidents · outcomes
Review · approve · investigate
Handle the decision at a checkpoint
Report a heartbeat, an actual run, and a useful outcome. A standalone heartbeat confirms contact but does not instrument the rest of your workflow. Docker and cloud workloads can use the same SDK or HTTP paths inside the environment you already operate.
No model-provider key or inbound port is required. Keep agent credentials in secure runner configuration, and send only the operational metadata needed for supervision.
An agent built with a framework can report through these paths when you can instrument its code or workflow. This is not a claim of a native connector to every agent framework. Controls require compatible checkpoints; monitoring alone does not add them.
Explore the separate Toolcaise Connect preview →START WITH ONE WORKFLOW
Connect the agent you already run. Build confidence from the work you can actually review.