Workflow Orchestration
Multi-step action chaining for DCC pipelines.
Overview
The workflow__run_chain tool lets an agent (or a human) execute a sequence
of dcc-mcp-core actions in order. Results from earlier steps flow into later
steps via context merging and {key} parameter interpolation.
Example: Select → Rename → Validate → Export
json{ "steps": [ { "label": "List mesh objects", "action": "maya_scene__list_objects", "params": {"type": "mesh"} }, { "label": "Rename with prefix", "action": "maya_scene__rename_objects", "params": {"prefix": "char_"} }, { "label": "Validate naming", "action": "maya_pipeline__validate_naming", "params": {} }, { "label": "Export FBX", "action": "maya_scene__export_fbx", "params": {"output": "/tmp/export.fbx"}, "stop_on_failure": true } ] }
Error Recovery
If a step fails and stop_on_failure is true, the chain halts immediately
and returns the partial results so far, plus the error details. The agent can
then use dcc_diagnostics__screenshot or dcc_diagnostics__audit_log to
investigate before retrying.
Context Interpolation
Use {key} placeholders in params to inject values from the running context:
json{"action": "export_fbx", "params": {"output": "{export_path}"}}
The context starts from the context input, then accumulates each step's
context output.
