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MCP Weather Assistant

MCP Weather Assistant

by yehudit-alfa
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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extract_weather_data_israel

Extract and clean current weather forecast text for Israel to provide real-time data for language models.

Instructions

מחלץ את תוכן דף התחזית הנוכחי, מנקה אותו ומחזיר את טקסט התחזית עבור ה-LLM.

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": "extract_weather_data_israel"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It states the tool extracts and cleans text, implying a read operation with no side effects, but it omits behavioral details like whether it requires prior navigation, what happens if no page is loaded, or the output format (though an output schema exists).

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?

The description is a single, clear Hebrew sentence that efficiently conveys the tool's action. It front-loads the verb and is free of unnecessary detail.

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?

For a tool with no parameters and an output schema, the description provides a basic understanding but lacks contextual completeness. It does not clarify the workflow (e.g., must be used after opening a forecast page) or error conditions. The sibling tools hint at a sequence, but the description alone is insufficient for an agent to know when invocation is valid.

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 input schema has zero parameters, so schema coverage is effectively 100%. The rules set a baseline of 4 for zero-parameter tools. The description adds no parameter information, which is acceptable since there are none to describe.

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?

The description clearly states the tool extracts, cleans, and returns forecast text from the current page. It uses verbs like 'extracts' and 'cleans', which distinguish it from sibling tools that 'enter', 'open', or 'select'. However, it could be more explicit about which specific forecast page is being referred to.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus its siblings. It does not mention prerequisites, such as needing to have navigated to a forecast page first, or that this should be called after using tools like open_weather_forecast_israel.

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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