render_project
Render the active multitrack CutPilot timeline with mixed audio and optional burned captions.
This record as markdown: /tools/cutpilot/render-project.md
What render_project does on Cutpilot
AI agents invoke render_project to trigger actions in Cutpilot. 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.
Why render_project is rated High
Rendering a timeline triggers a substantial external compute operation that produces output files (video with mixed audio and optionally burned-in captions). This is an Execute-class action because it runs a complex processing pipeline whose effects depend on the current timeline state and arguments (caption burning).
From the tool's definition "Render the active multitrack CutPilot timeline with mixed audio and optional burned captions"
Attacks that exploit this kind of access
The rule that runs render_project safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Cutpilot, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For render_project, this is the rule to start with:
render_project 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 Cutpilot, apply this rule, and every render_project call is checked against it from then on.
Questions about render_project
Render the active multitrack CutPilot timeline with mixed audio and optional burned captions. It is categorised as a Execute tool in the Cutpilot MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Cutpilot MCP server in PolicyLayer and add a rule for render_project: 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 Cutpilot. Nothing to install.
render_project 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 render_project 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 render_project. 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.
render_project is provided by the Cutpilot MCP server (Hellotravisss/cutpilot). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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