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Weather-MCP

Weather-MCP

by Efrat-Fr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_weather_forecast_content_israel

Extract and clean weather forecast text from the open Israel forecast page to answer user queries directly.

Instructions

Extract the weather forecast text from the currently open forecast page.

Returns the cleaned textual content so the LLM can answer the user directly.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_weather_forecast_content_israel"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that the tool extracts and cleans text and returns it for direct answering, which is useful. However, it does not specify failure behavior (e.g., what happens if no forecast page is open) or what 'cleaned' means concretely, leaving some behavioral uncertainty.

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, no filler. The core purpose is front-loaded, and the second sentence explains why the output matters to the agent. Every word earns its place.

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

Completeness4/5

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

For a zero-parameter extraction tool with an output schema, the description is largely complete: it states the source, the output type, and the intended use. It could be slightly stronger by explicitly advising that it should follow open_weather_forecast_israel or similar navigation tools, but 'currently open forecast page' conveys this adequately.

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

Parameters4/5

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

The tool has zero parameters and the schema is fully complete with an empty properties object. The description correctly relies on page state rather than parameters, and no additional parameter explanation is needed. The baseline of 4 for zero-parameter tools applies.

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

Purpose5/5

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

Description states a specific verb (Extract) and resource (weather forecast text from the currently open forecast page), and clarifies the output is cleaned textual content for direct LLM answering. This clearly separates it from sibling tools that open or select forecast pages, since it operates on the already-open page.

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

Usage Guidelines4/5

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

The phrase 'currently open forecast page' establishes the key precondition: this tool should be used after a forecast page has been opened, not before. It does not explicitly name alternatives or exclusion conditions, but the context of opening/selecting pages among siblings makes the intended usage inferable.

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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