Skip to main content
Glama
bhujangarao-db

weather-mcp-server

by bhujangarao-db
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
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: Weather MCP 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

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It communicates a read-only retrieval operation and the scope of returned data, but it does not disclose data source assumptions, units, timezone/freshness behavior, or error handling. This is adequate for a simple read tool but not deeply transparent.

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 compact and well-structured: a one-sentence main behavior followed by two focused argument descriptions. Every sentence earns its place, and the behavioral summary is front-loaded.

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 simple two-parameter weather tool with an output schema available, the description covers the essential call semantics. The main omissions are environmental details like units, timezone, and data freshness, which are not strictly required for invoking the tool correctly.

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 description coverage is 0%, and the description fully compensates. It explains that location is a city, region, or country name with concrete examples, and it clarifies forecast_days as a 1-through-7 range, adding real meaning beyond the bare string/integer schema types.

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 states a specific verb and resource: 'Get current conditions and a weather forecast for a place.' It clearly distinguishes the output scope (current conditions plus forecast), though it does not need to differentiate from siblings because none are listed.

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?

Usage context is implied: an agent would use this tool when current weather or a forecast is needed for a location. However, there is no explicit when-to-use vs alternatives, no exclusions, and no edge-case guidance such as ambiguous location handling.

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. Dates show when Glama detected each change.

  1. 1 tool updatev0.1.0
    • First observedget_weather
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4/5.0
Disambiguation5/5

Only one tool exists, so there is no possibility of confusing it with another. The tool's purpose is clearly defined and distinct.

Naming Consistency5/5

The single tool uses a clear, conventional verb_noun pattern (get_weather), which is consistent and intuitive. There are no naming inconsistencies to evaluate.

Tool Count3/5

A single tool for a weather server is minimal but borderline acceptable because it combines current conditions and forecast. However, it feels thin compared to the typical scope of a weather-focused MCP server.

Completeness4/5

The tool covers the core weather needs—current conditions and forecast—with configurable forecast days. Missing features like alerts or historical data are minor gaps that agents can work around for basic weather queries.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/bhujangarao-db/mcp-server-app-v1'

If you have feedback or need assistance with the MCP directory API, please join our Discord server