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BACH-AI-Tools

Open Weather13 MCP Server

by BACH-AI-Tools
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

v2

Retrieve 5-day weather forecasts using latitude and longitude coordinates, with support for multiple languages.

Instructions

Get 5 days weather forecast data by Latitude \u0026 Longitude

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeYesExample value: 40.730610
longitudeYesExample value: -73.935242
langNoWe support the following languages that you can use with the corresponded lang values: AFAfrikaans, ALAlbanian, ARArabic, AZAzerbaijani, BGBulgarian, CACatalan, CZCzech, DADanish, DEGerman, ELGreek, ENEnglish, EUBasque, FAPersian (Farsi), FIFinnish, FRFrench, GLGalician, HEHebrew, HIHindi, HRCroatian, HUHungarian, IDIndonesian, ITItalian, JAJapanese, KRKorean, LALatvian, LTLithuanian, MKMacedonian, NONorwegian, NLDutch, PLPolish, PTPortuguese, PT_BRPortuguês Brasil, RORomanian, RURussian, SESwed

Implementation Reference

  • server.py:56-61 (registration)
    The tool is automatically registered by FastMCP from the OpenAPI specification provided in OPENAPI_SPEC. The tool names are derived from the operationIds in the specification (e.g., v2___3_hour_forecast_5_days).
    mcp = FastMCP.from_openapi(
    openapi_spec=openapi_dict,
    client=client,
    name="open_weather13",
    version=__version__
)

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool fetches forecast data but lacks details on rate limits, authentication needs, error handling, or data format. The description is minimal and does not compensate for the absence of annotations, leaving key behavioral traits unspecified.

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, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core purpose, making it easy to parse and understand quickly.

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

Completeness2/5

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

Given the complexity of a weather API tool with no annotations and no output schema, the description is insufficient. It lacks details on response format, error conditions, or any behavioral nuances. While the input schema is well-documented, the description does not provide enough context for an agent to fully understand how to use the tool effectively.

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?

The description adds minimal semantic context beyond the input schema. It implies latitude and longitude are required for fetching weather data, but the schema already has 100% coverage with detailed descriptions (including examples for latitude/longitude and a language list for 'lang'). The description does not explain parameter interactions or provide additional insights, so it meets the baseline for high schema coverage.

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's purpose: 'Get 5 days weather forecast data by Latitude & Longitude'. It specifies the verb ('Get'), resource ('weather forecast data'), and scope ('5 days', 'by Latitude & Longitude'). However, it does not differentiate from sibling tools v2_2 and v2_3, which likely offer similar or related weather data services.

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?

The description provides no guidance on when to use this tool versus its siblings (v2_2, v2_3) or any alternatives. It states what the tool does but offers no context about prerequisites, limitations, or comparative use cases, leaving the agent to infer usage scenarios.

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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