High Risk →

summarize_video

Start here. Get a compact overview of a video: metadata, which features are indexed, a transcript preview, and scene count. Use this to decide which tools to call next — then use segment_video to detect specific objects in time ranges of interest.

Part of the Reka server.

summarize_video can trigger actions in Reka, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke summarize_video to trigger processes or run actions in Reka. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

summarize_video can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

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

See the full Reka policy for all 17 tools.

Get this rule live on your own Reka server in minutes. PolicyLayer enforces it on every call, before it runs.

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View all 17 tools →

These attack patterns abuse exactly the kind of access summarize_video gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so summarize_video only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the summarize_video tool do? +

Start here. Get a compact overview of a video: metadata, which features are indexed, a transcript preview, and scene count. Use this to decide which tools to call next — then use segment_video to detect specific objects in time ranges of interest.. It is categorised as a Execute tool in the Reka MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on summarize_video? +

Register the Reka MCP server in PolicyLayer and add a rule for summarize_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 Reka. Nothing to install.

What risk level is summarize_video? +

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

Can I rate-limit summarize_video? +

Yes. Add a rate_limit block to the summarize_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 summarize_video completely? +

Set action: deny in the PolicyLayer policy for summarize_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 summarize_video? +

summarize_video is provided by the Reka MCP server (pypi:reka-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Reka tool call.

Deterministic rules across all 17 Reka tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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