JMA Data MCP

Get Weather Time Series

get_weather_time_series

Read-onlyIdempotent

Fetches time-series weather data for a specified JMA station, enabling analysis of hourly or daily trends over a chosen period.

Instructions

Get time series weather data for a station.

Useful for analyzing weather trends over hours or days.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "station_code": "<station_code>"
    },
    "name": "get_weather_time_series"
  }
}

Input Schema

Name	Required	Description
`hours`	No	Number of hours to fetch (default: 24, max: 168 for ~1 week)
`station_code`	Yes	Station code (e.g., '44132' for Tokyo)
`interval_minutes`	No	Interval between data points in minutes (10, 30, or 60)

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv0.2.1May 1, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```
- addedInput schema / properties / hours / description
```
Added value: +"Number of hours to fetch (default: 24, max: 168 for ~1 week)"
```
- addedInput schema / properties / interval_minutes / description
```
Added value: +"Interval between data points in minutes (10, 30, or 60)"
```
- addedInput schema / properties / station_code / description
```
Added value: +"Station code (e.g., '44132' for Tokyo)"
```
First observedDec 19, 2025

TDQS

A3.5/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is fully covered. The description adds only a vague granularity hint ('over hours or days'); it says nothing about data source, latency, pagination, or limits beyond the schema's max of 168 hours. Non-contradictory but thin.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, purpose front-loaded, zero filler. Nothing to trim.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema and rich annotations relieve the description of return-value and safety duties, and the schema fully covers parameters. The remaining gap is the unresolved overlap with get_historical_weather, which an agent needs in order to pick the right tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% — all three parameters are documented with defaults, examples, and constraints (10/30/60 interval, max 168 hours). The description adds no parameter meaning beyond that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get time series weather data') and scopes it to a station, which separates it from get_current_weather and get_forecast. However, it never names or contrasts with get_historical_weather, the closest sibling, so an agent must infer the boundary between 'time series' and 'historical'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Useful for analyzing weather trends over hours or days' implies a use case but gives no explicit when-to-use/when-not, no alternative named, and no hint about how it differs from get_forecast or get_historical_weather.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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