render_glsl_batch
Render multiple validated GLSL video jobs concurrently through independent local Chrome WebGL1 workers, preserving a durable batch manifest and per-job errors.
This record as markdown: /tools/cutpilot/render-glsl-batch.md
What render_glsl_batch does on Cutpilot
AI agents invoke render_glsl_batch 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_glsl_batch is rated High
This tool executes rendering jobs — running GLSL shader code through Chrome WebGL workers. It triggers external computation (spawning browser workers, executing shader programs) whose effects depend on the job arguments. The batch nature and concurrent execution increase the blast radius, as misuse could spawn many resource-intensive processes or render malicious shader code.
From the tool's definition 'Render multiple validated GLSL video jobs concurrently through independent local Chrome WebGL1 workers'
Attacks that exploit this kind of access
The rule that runs render_glsl_batch 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_glsl_batch, this is the rule to start with:
render_glsl_batch 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_glsl_batch call is checked against it from then on.
Questions about render_glsl_batch
Render multiple validated GLSL video jobs concurrently through independent local Chrome WebGL1 workers, preserving a durable batch manifest and per-job errors. 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_glsl_batch: 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_glsl_batch 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_glsl_batch 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_glsl_batch. 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_glsl_batch 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.
More on Cutpilot, and thousands of servers like it.
Across the catalogue