Probabilistic ensemble weather forecast — up to 51 ensemble members, up to 16 days ahead with optional past_days (0–92). Each member's values appear as separate columns named with a member suffix (e.g. temperature_2m_member01, temperature_2m_member02). Use the spread across members to compute exc...
Risk signalsHigh parameter count (12 properties)
Part of the Open Meteo Mcp Server server.
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AI agents call openmeteo_get_ensemble 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_get_ensemble 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.
{
"version": "1",
"default": "deny",
"tools": {
"openmeteo_get_ensemble": {}
}
}See the full Open Meteo Mcp Server policy for all 10 tools.
These attack patterns abuse exactly the kind of access openmeteo_get_ensemble gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Probabilistic ensemble weather forecast — up to 51 ensemble members, up to 16 days ahead with optional past_days (0–92). Each member's values appear as separate columns named with a member suffix (e.g. temperature_2m_member01, temperature_2m_member02). Use the spread across members to compute exceedance probabilities, quantify forecast uncertainty, and build decision thresholds. Available models: "ecmwf_ifs025" (51 members, global, 0.25°), "gfs025" (31 members, global, 0.25°), "icon_seamless" (40 members, global/Europe blend), "gem_global" (21 members, global, 0.25°). Omit models to use the API default blend. Large multi-member, multi-day pulls produce thousands of records and spill to DataCanvas when canvas is enabled. At least one of hourly_variables or daily_variables is required.. It is categorised as a Read tool in the Open Meteo Mcp Server MCP Server, which means it retrieves data without modifying state.
Register the Open Meteo Mcp Server MCP server in PolicyLayer and add a rule for openmeteo_get_ensemble: 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.
openmeteo_get_ensemble is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the openmeteo_get_ensemble 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.
Set action: deny in the PolicyLayer policy for openmeteo_get_ensemble. 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.
openmeteo_get_ensemble 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.
Deterministic rules across all 10 Open Meteo Mcp Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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