The coding loop is the unusual part: it writes Python, runs it, and saves the working block into the pipeline as an integration — alongside the ordinary work of querying events, driving jobs and sending decision feedback back to the model.
A management and query client for Arcanna's AI use cases. It reads processed events with filters, creates and controls jobs and integrations, feeds decision feedback back into the model, and generates, executes and saves Python as an Arcanna integration.
- Events processed by Arcanna, queried with multiple filters, plus the field list to build those filters from
- Jobs and integrations created, updated, retrieved and deleted
- The parameter schema an integration expects
- Jobs started, stopped and trained
- Feedback attached to an event's decision, so model accuracy moves on real corrections
- Python generated, executed, and saved into the pipeline as an integration
- A health check covering the server and the API key
An Arcanna host and a management API key, both passed in the client config. Runs from the published Docker image or the PyPI package; Docker is the documented path.
One command plus a key — docker run -i --rm -e ARCANNA_MANAGEMENT_API_KEY -e ARCANNA_HOST arcanna/arcanna-mcp-server, then supply credentials