High Risk →

generate_image_to_video

Generates a video from an image using RunwayML or Luma AI.

How to control generate_image_to_video ↓

What generate_image_to_video does on RunwayML + Luma AI MCP Server

AI agents invoke generate_image_to_video to trigger actions in RunwayML + Luma AI MCP Server. 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.

High Risk

Why generate_image_to_video needs a policy

This tool initiates an external computational operation (video generation) via RunwayML or Luma AI APIs. It is not a simple read, nor does it delete data or move money. The effects depend on the input image and parameters passed, and it triggers real API calls that consume credits/quota.

From the tool's definition 'Generates a video from an image using RunwayML or Luma AI' — triggers an external AI generation operation on a third-party API

Documented attack patterns abuse exactly the kind of access generate_image_to_video gives an agent:

How to control generate_image_to_video

PolicyLayer is an MCP gateway — it sits between your AI agents and RunwayML + Luma AI MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for generate_image_to_video:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "generate_image_to_video": {
      "limits": [
        {
          "counter": "generate_image_to_video_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

generate_image_to_video 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.

  1. Create a free account and register RunwayML + Luma AI MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
RATE-LIMIT THIS TOOL →

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Related tools and policies

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Questions about generate_image_to_video

What does the generate_image_to_video tool do? +

Generates a video from an image using RunwayML or Luma AI. It is categorised as a Execute tool in the RunwayML + Luma AI MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on generate_image_to_video? +

Register the RunwayML + Luma AI MCP Server MCP server in PolicyLayer and add a rule for generate_image_to_video: 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 RunwayML + Luma AI MCP Server. Nothing to install.

What risk level is generate_image_to_video? +

generate_image_to_video is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit generate_image_to_video? +

Yes. Add a rate_limit block to the generate_image_to_video 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.

How do I block generate_image_to_video completely? +

Set action: deny in the PolicyLayer policy for generate_image_to_video. 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.

What MCP server provides generate_image_to_video? +

generate_image_to_video is provided by the RunwayML + Luma AI MCP Server MCP server (wheattoast11/mcp-video-gen). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every RunwayML + Luma AI MCP Server tool call.

Start from RunwayML + Luma AI MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

10 RunwayML + Luma AI MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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