How can an AI agent control Unreal Engine?

An MCP-compatible AI agent can use DCC-MCP to inspect projects and automate levels, actors, assets, Blueprints, tests, and packaged builds. 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.

Unreal Engine MCP and Unreal Engine CLI

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

dcc-mcp-cli search --query "inventory maps, actors, assets, and project settings" --dcc-type unreal

What can an AI agent do in Unreal Engine?

• inventory maps, actors, assets, and project settings.
• build one bounded gameplay or editor workflow.
• run and verify the result before packaging.

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 Unreal Engine 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 Unreal Engine 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 "build one bounded gameplay or editor workflow", 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: "run and verify the result before packaging". Report the instance, tool, result, and evidence path.

Current availability and official source

The current catalog lists unreal 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.

• Unreal Engine 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.