weather_climate_intel

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io

Low RISK CLASS

Category Read

Parameters 62 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/weather-climate-intel.md

WHAT IT DOES

What weather_climate_intel does on Mcp Knowledge

AI agents call weather_climate_intel to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Parameter	Type	Required	Description
`mode`	string	Yes	'forecast' (14 days), 'historical' (date range since 1940), 'climate_risk' (long-term physical risk score)
`async`	boolean	—	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti
`date_to`	string	—	ISO date YYYY-MM-DD — end of date range (required for historical/climate_risk)
`metrics`	array	—	Weather metrics to include. Default: all metrics.
`location`	object	Yes	Geographic location. Provide either {city, country?} or {lat, lon}.
`date_from`	string	—	ISO date YYYY-MM-DD — start of date range (required for historical/climate_risk)

Parameters from the server's own tool schema.

RISK

Why weather_climate_intel is rated Low

All three modes retrieve and return data (weather forecasts, historical records, climate risk scores). There are no side effects, no data modification, no code execution, and no financial transactions. The tool purely queries and delivers climate/weather intelligence.

From the tool's definition forecast — 14-day daily weather forecast; historical — daily records and monthly aggregates; climate_risk — long-term physical risk scoring combining CMIP6 ensemble projections

Risk signalsHigh parameter count (10 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs weather_climate_intel safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For weather_climate_intel, this is the rule to start with:

weather_climate_intel Allowed

weather_climate_intel is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "weather_climate_intel": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every weather_climate_intel call is checked against it from then on.

FAQ

Questions about weather_climate_intel

What does the weather_climate_intel tool do? +

Physical climate intelligence for insurance underwriting, agritech, logistics, energy trading and ESG/climate risk disclosure. Three modes: (1) forecast — 14-day daily weather forecast with temperature, precipitation, wind and humidity; (2) historical — daily records and monthly aggregates for any date range since 1940, with anomaly detection (P90/P95 heat events, extreme precipitation days); (3) climate_risk — long-term physical risk scoring combining CMIP6 ensemble projections (2020-2050), altitude, FEMA flood zones (US) and historical baselines. Risk dimensions: flood, heat (days >35°C/year), drought (SPI), wildfire, sea-level. Overall score 0-100 (100 = severe). Location: city string or lat/lon coordinates. Sources: Open-Meteo (keyless, global, 1940→2050), Open-Elevation, FEMA NFHL (US), NOAA CDO (optional NOAA_API_KEY env var for US+global station data). SLA: ≤25s p95. Cache: 1h forecast / 24h historical / 7d climate_risk. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.

What parameters does weather_climate_intel accept? +

weather_climate_intel accepts 6 parameters: mode, async, date_to, metrics, location, date_from. Required: mode, location. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on weather_climate_intel? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for weather_climate_intel: 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 Mcp Knowledge. Nothing to install.

What risk level is weather_climate_intel? +

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

Can I rate-limit weather_climate_intel? +

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

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

weather_climate_intel is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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