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Weather MCP Server

by minidantre-db
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Python
Remote

Weather MCP Server

A Python Model Context Protocol server that gives an AI current weather and forecasts. It geocodes locations and reads forecast data from Open-Meteo, then optionally uses Groq to explain the result naturally.

Requirements

  • Python 3.11 or newer

  • A Groq API key for AI-generated summaries

  • Internet access for Open-Meteo and Groq requests

Related MCP server: mcp-weather-server

Setup

PowerShell:

py -3.11 -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"
Copy-Item .env.example .env

Open .env and set GROQ_API_KEY. The server still works without the key, but it returns structured JSON instead of an AI summary.

Run

Browser UI

Start the user-facing weather chat:

python -m weather_mcp_server.web

Then open http://127.0.0.1:8000. Ask questions such as “Will it rain in London tomorrow?” The browser sends the question to the web adapter, which invokes the same get_weather tool exposed by the MCP server.

Run the server directly:

python -m weather_mcp_server.server

MCP clients can use the checked-in .vscode/mcp.json configuration. In VS Code, open this folder as the workspace, install the Python extension if prompted, and start the weather-mcp-server MCP server from the MCP controls.

The server exposes one tool:

  • get_weather(location, forecast_days=3): returns current conditions and 1-7 days of forecast data.

Test

python -m pytest

The tests mock Open-Meteo, so they do not require network access or a Groq key.

Available Tools

1 tool
get_weatherA

Get current conditions and a weather forecast for a place.

Args: location: A city, region, or country name, such as "London" or "Tokyo". forecast_days: Number of forecast days to return, from 1 through 7.

ParametersJSON Schema
NameRequiredDescriptionDefault
locationYes
forecast_daysNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.3/5.0
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 of behavioral disclosure. It conveys the read-only nature of the operation and the high-level output (current conditions and forecast), but it does not mention units, error handling, or what the forecast includes, leaving some behavioral ambiguity.

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 two sentences plus a two-item Args list. The main purpose is front-loaded, and every line adds either scope or parameter detail, with no filler.

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?

With only two parameters, one of which has a default, and an output schema present, the description covers the necessary input semantics and high-level behavior. Gaps like unit conventions are minor given the output schema, so the description is nearly complete.

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

Parameters5/5

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

Schema coverage is 0%, yet the description's Args section fully compensates: it defines 'location' as a city, region, or country with examples, and 'forecast_days' as a range from 1 through 7. This adds meaningful semantics beyond the bare schema properties.

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?

The description opens with 'Get current conditions and a weather forecast for a place,' which names a specific action (get) and resource (conditions + forecast). This clearly distinguishes the tool's function even in the absence of siblings.

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 description clearly communicates that the tool is for retrieving weather data for a location, and the Args section explains how to supply the location and optional forecast length. Since there are no sibling tools, explicit when-not or alternative guidance is unnecessary; the implied usage context is sufficient.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.1.0
    • First observedget_weather
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.4/5.0

Scored across 1 tool

Disambiguation5/5

With only a single tool, there is no possibility of ambiguity or confusion between different functions.

Naming Consistency5/5

The single tool name 'get_weather' follows a clear, conventional verb_noun pattern, consistent with common MCP naming practices.

Tool Count3/5

One tool is at the lower boundary of what is reasonable for a weather server; it feels slightly thin but not entirely inadequate given the combined current/forecast functionality.

Completeness2/5

The tool covers basic conditions and forecast but lacks common weather-related operations such as alerts, historical data, or location management, leaving notable gaps for a full-featured weather service.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • Weather MCP Server

    JeremyMorgan
    A
    license
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    Enables AI assistants to retrieve current weather, forecasts, and summaries for any global location using the Open-Meteo API, with no API key required.
    13 npm
    Creative Commons Zero v1.0 Universal

  • mcp-weather-server

    srathish
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    quality
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    Provides live weather data (current conditions, forecasts) and city geocoding through Open-Meteo API, enabling AI assistants to answer weather queries without an API key.
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  • weather-mcp-server

    itachiuchihadev
    A
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    Provides weather forecasts and geocoding lookup using free Open-Meteo APIs, enabling LLMs to query real-time weather and multi-day forecasts for any location.
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  • mcp-weather

    pipeworx-io
    A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI agents to retrieve real-time weather conditions and 7-10 day forecasts for any location via Open-Meteo, with no API key required.
    157 npm
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