neuron_studio_make
One-shot: build/edit a video from a prompt AND start the MP4 render. Returns the ProjectDoc, the edits, and a render job — poll it with neuron_studio_render_status until status is 'completed' to get the outputUrl. Great for 'make me a 20s TikTok reel about X'. Requires a Pro+ plan.
This record as markdown: /tools/io-github-conquext-neuron/neuron-studio-make.md
What neuron_studio_make does on Neuron
AI agents invoke neuron_studio_make to trigger actions in Neuron. 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 |
|---|---|---|---|
doc | object | — | An existing Studio ProjectDoc to edit. Omit to start a fresh video. |
model | string | — | Override the studio model id (else the org/default is used). |
platform | string | — | Canvas size for a NEW video (default instagram-story 9:16). Use tiktok/instagram-story for a reel. |
instruction | string | Yes | Plain-English description of the video to build or the edit to make. |
durationSeconds | number | — | Length of a NEW blank video in seconds (default 5). |
Parameters from the server's own tool schema.
Why neuron_studio_make is rated High
neuron_studio_make triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs neuron_studio_make safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Neuron, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For neuron_studio_make, this is the rule to start with:
neuron_studio_make 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 Neuron, apply this rule, and every neuron_studio_make call is checked against it from then on.
Questions about neuron_studio_make
One-shot: build/edit a video from a prompt AND start the MP4 render. Returns the ProjectDoc, the edits, and a render job — poll it with neuron_studio_render_status until status is 'completed' to get the outputUrl. Great for 'make me a 20s TikTok reel about X'. Requires a Pro+ plan. It is categorised as a Execute tool in the Neuron MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
neuron_studio_make accepts 5 parameters: doc, model, platform, instruction, durationSeconds. Required: instruction. The full parameter table on this page comes from the server's own tool schema.
Register the Neuron MCP server in PolicyLayer and add a rule for neuron_studio_make: 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 Neuron. Nothing to install.
neuron_studio_make 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 neuron_studio_make 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 neuron_studio_make. 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.
neuron_studio_make is provided by the Neuron MCP server (neuron-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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