resize_video · FFmpeg Python MCP Server MCP: Risk & Policy

WHAT IT DOES

What resize_video does on FFmpeg Python MCP Server

AI agents use resize_video to create or update resources in FFmpeg Python MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FFmpeg Python MCP Server environment.

WHY IT NEEDS A POLICY

Why resize_video needs a policy

Resizing video creates a new or modified file output, which is a Write operation. It is not Destructive because the original source file typically remains intact and the operation is reversible by re-processing. It is not Execute because it doesn't run arbitrary code—it applies a specific, constrained transformation.

From the tool's definition Tool performs video resolution modification (resize_video: 调整视频分辨率 = 'adjust video resolution'). This modifies the output video file without permanently destroying the original data if the operation is reversible through re-processing.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

resize_video Rate-limited

resize_video stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "resize_video": {
      "limits": [
        {
          "counter": "resize_video_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches FFmpeg Python MCP Server, so you can run agents against it safely.

FAQ

Questions about resize_video

What does the resize_video tool do? +

调整视频分辨率. It is categorised as a Write tool in the FFmpeg Python MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on resize_video? +

Register the FFmpeg Python MCP Server MCP server in PolicyLayer and add a rule for resize_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 FFmpeg Python MCP Server. Nothing to install.

What risk level is resize_video? +

resize_video is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit resize_video? +

Yes. Add a rate_limit block to the resize_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 resize_video completely? +

Set action: deny in the PolicyLayer policy for resize_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 resize_video? +

resize_video is provided by the FFmpeg Python MCP Server MCP server (mabh111111/ffmpeg_python_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.