start_trace
Start an Unreal Insights trace session with selected channels.
This record as markdown: /tools/jjpxdev-unreal-mcp/start-trace.md
What start_trace does on Unreal
AI agents invoke start_trace to trigger actions in Unreal. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
channels | array | — | Trace channels: cpu, gpu, frame, memory, counters, bookmark, file, net, loadtime |
Parameters from the server's own tool schema.
Why start_trace is rated High
This tool executes a profiling/tracing operation in Unreal Engine, which is an external system action. While not destructive or permanently modifying data, trace sessions consume resources and affect system state during their execution. The action is triggered by the tool call and its effects depend on parameters (selected channels).
From the tool's definition Tool name is 'start_trace' and description states it 'Start[s] an Unreal Insights trace session with selected channels.' Starting a trace session triggers external profiling/monitoring operations whose runtime behavior and resource consumption depend on…
Attacks that exploit this kind of access
The rule that runs start_trace safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Unreal, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For start_trace, this is the rule to start with:
start_trace stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Unreal, apply this rule, and every start_trace call is checked against it from then on.
Questions about start_trace
Start an Unreal Insights trace session with selected channels. It is categorised as a Execute tool in the Unreal MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
start_trace accepts 1 parameter: channels. The full parameter table on this page comes from the server's own tool schema.
Register the Unreal MCP server in PolicyLayer and add a rule for start_trace: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Unreal. Nothing to install.
start_trace is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the start_trace rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for start_trace. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
start_trace is provided by the Unreal MCP server (@jjpxdev/unreal-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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