How can an AI agent control Flow Production Tracking?

An MCP-compatible AI agent can use DCC-MCP to query production entities and safely update approved tasks, notes, versions, and status. The agent selects the correct application instance or integration, discovers available tools, and reads their parameter definitions before acting and checking the result. These typed tools declare their inputs, outputs, and parameter types.

Flow Production Tracking MCP and Flow Production Tracking CLI

The Flow Production Tracking MCP endpoint and Flow Production Tracking CLI workflow share the same DCC-MCP adapter and tool catalog. Use dcc-mcp-cli with --dcc-type shotgrid to limit tool searches to Flow Production Tracking. Tools declare their inputs, outputs, and parameter types so arguments can be checked before a call.

dcc-mcp-cli search --query "find a project, shot, asset, or task" --dcc-type shotgrid

What can an AI agent do in Flow Production Tracking?

• find a project, shot, asset, or task.
• summarize linked notes and versions.
• preview and confirm any status-changing write.

Capabilities change with the adapter version and loaded Skills. Search and describe tools first instead of guessing current tool names from this page.

Safe operating flow

1. Install and follow the public dcc-mcp Skill.
2. Inspect the existing CLI, adapter, and live hosts; obtain consent before installing software or changing system state.
3. Use health, dcc-types, and list to verify the Gateway and target instance.
4. Search and describe tools for the actual Flow Production Tracking task, then follow every returned next_step.
5. Make one bounded change and verify it through host state, files, previews, logs, or rendered output.

dcc-mcp-cli health
dcc-mcp-cli dcc-types
dcc-mcp-cli list

Copyable prompt

Use the dcc-mcp Skill to connect to my Flow Production Tracking session. Inspect the existing CLI, adapter, and live instance first; ask before installing software or changing system state. Search for and describe typed tools related to "summarize linked notes and versions", then follow every returned next_step. Do not delete, overwrite, or publish existing work. Make the smallest verifiable change, then check the result against this requirement: "preview and confirm any status-changing write". Report the instance, tool, result, and evidence path.

Current availability and official source

The current catalog lists shotgrid as the adapter identifier. Catalog definitions do not establish host acceptance; run dcc-mcp-cli dcc-types, then discover and describe the live instance's tools before operating.

• Flow Production Tracking adapter repository: source of truth for installation, compatibility, host-specific capabilities, and troubleshooting.
• All AI + DCC control guides: return to every public application and pipeline integration.
• Agent workflow: shared discovery, call, validation, and diagnostic steps.

This page describes the shared Agent workflow. Each integration's repository owns its installation, API, and compatibility details.