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Install

Cascades in ChatGPT

  1. ChatGPT connectors only speak remote MCP (a hosted Streamable-HTTP endpoint with OAuth). The Cascades server ships as a local stdio binary today, so there is nothing to paste yet.
  2. A hosted endpoint with per-user authorization is on the roadmap; this page will carry the connector URL when it exists.
  3. In the meantime, use Claude Code, Claude Desktop, Cursor, VS Code or Windsurf — all of which run the local server.

Notes

  • Do not expose the server's HTTP mode (MCP_TRANSPORT=http) to the internet to work around this: it serves every caller with one process-level key and has no per-request auth.

What you get

Tool What it does Access REST call
cascades_create_workflow Create a new cascade (decision workflow) from a JSON definition, owned by the API key's account. write POST /workflows
cascades_delete_workflow Delete a cascade (soft-delete). destructive DELETE /workflows/{id}
cascades_generate_workflow Build a cascade from a plain-English policy description using the Cascades AI builder, then create it (by default) so it is immediately runnable with cascades_trigger_workflow. write POST /workflows/generate
cascades_get_execution Fetch a single cascade execution by id to check its status and results. read GET /executions/{id}
cascades_get_workflow Fetch one cascade by id, including its full node graph (`definition`). read GET /workflows/{id}
cascades_list_test_cases List the pre-registered sandbox test-case subjects for a cascade — the synthetic applicants the CRS Testcase Service has authored for that cascade's products (e.g. specific credit-score bands). read GET /workflows/{id}/test_cases
cascades_list_workflows List the caller's saved Cascades (decision workflows) — their id, code, name, use_case, trigger_type, and whether each is active. read GET /workflows
cascades_trigger_workflow Run a saved cascade for an applicant — i.e. start a decision. write POST /workflows/{id}/trigger
cascades_update_workflow Update an existing cascade. write PATCH /workflows/{id}