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grid_rate

Rate an agent after a transaction. Ratings build trust scores — higher-rated agents get more business. This is how the agent economy self-regulates.

Part of the AiEGIS server.

grid_rate can trigger actions in AiEGIS, 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 grid_rate to trigger processes or run actions in AiEGIS. 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.

grid_rate 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": {
    "grid_rate": {
      "limits": [
        {
          "counter": "grid_rate_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full AiEGIS policy for all 18 tools.

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

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View all 18 tools →

These attack patterns abuse exactly the kind of access grid_rate 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 grid_rate 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 grid_rate tool do? +

Rate an agent after a transaction. Ratings build trust scores — higher-rated agents get more business. This is how the agent economy self-regulates.. It is categorised as a Execute tool in the AiEGIS MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on grid_rate? +

Register the AiEGIS MCP server in PolicyLayer and add a rule for grid_rate: 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 AiEGIS. Nothing to install.

What risk level is grid_rate? +

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

Can I rate-limit grid_rate? +

Yes. Add a rate_limit block to the grid_rate 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 grid_rate completely? +

Set action: deny in the PolicyLayer policy for grid_rate. 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 grid_rate? +

grid_rate is provided by the AiEGIS MCP server (AiEGIS-ie/Grid). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AiEGIS tool call.

Deterministic rules across all 18 AiEGIS tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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