Low Risk

aggregate_data

Aggregate dataset rows by 1-3 columns with optional metrics (sum, avg, min, max, count). Defaults to counting unique values.

Part of the Opendata Ademe server.

aggregate_data is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call aggregate_data to retrieve information from Opendata Ademe without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though aggregate_data only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "aggregate_data": {}
  }
}

See the full Opendata Ademe policy for all 6 tools.

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

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These attack patterns abuse exactly the kind of access aggregate_data 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 aggregate_data only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the aggregate_data tool do? +

Aggregate dataset rows by 1-3 columns with optional metrics (sum, avg, min, max, count). Defaults to counting unique values.. It is categorised as a Read tool in the Opendata Ademe MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on aggregate_data? +

Register the Opendata Ademe MCP server in PolicyLayer and add a rule for aggregate_data: 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 Opendata Ademe. Nothing to install.

What risk level is aggregate_data? +

aggregate_data is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit aggregate_data? +

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

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

aggregate_data is provided by the Opendata Ademe MCP server (koumoul/ademe-opendata). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Opendata Ademe tool call.

Deterministic rules across all 6 Opendata Ademe tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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