Low Risk

openmeteo_dataframe_query

Run a read-only SQL SELECT against tables staged on a DataCanvas by openmeteo_get_historical. Pass the canvas_id returned when openmeteo_get_historical spills (truncated: true). Tables are named by the spillover helper (e.g. spilled_<id>); use openmeteo_dataframe_describe to list available tables...

Risk signalsAccepts freeform code/query input (sql)

Part of the Open Meteo Mcp Server server.

openmeteo_dataframe_query 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 openmeteo_dataframe_query to retrieve information from Open Meteo Mcp Server 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 openmeteo_dataframe_query 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": {
    "openmeteo_dataframe_query": {}
  }
}

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

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so openmeteo_dataframe_query 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 openmeteo_dataframe_query tool do? +

Run a read-only SQL SELECT against tables staged on a DataCanvas by openmeteo_get_historical. Pass the canvas_id returned when openmeteo_get_historical spills (truncated: true). Tables are named by the spillover helper (e.g. spilled_<id>); use openmeteo_dataframe_describe to list available tables and their columns before querying.. It is categorised as a Read tool in the Open Meteo Mcp Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on openmeteo_dataframe_query? +

Register the Open Meteo Mcp Server MCP server in PolicyLayer and add a rule for openmeteo_dataframe_query: 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 Open Meteo Mcp Server. Nothing to install.

What risk level is openmeteo_dataframe_query? +

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

Can I rate-limit openmeteo_dataframe_query? +

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

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

openmeteo_dataframe_query is provided by the Open Meteo Mcp Server MCP server (@cyanheads/open-meteo-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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