weather-mcp

A minimal Model Context Protocol server in a single file. It speaks JSON-RPC 2.0 over stdio and exposes two tools, get_weather and get_hourly_forecast, backed by the free Open-Meteo API.

No third-party dependencies — standard library only. Requires Python 3.7+.

The tools

Usage

Once the server is wired into a client (see below), just ask in natural language — the model picks the tool and fills in the arguments:

You: What's the weather in Seattle right now?

Claude: (calls get_weather with location: "Seattle") Current weather in Seattle, United States: overcast, 54.2 °F, wind 1.1 mph.

You: Will it rain in Tokyo over the next 6 hours?

Claude: (calls get_hourly_forecast with location: "Tokyo", hours: 6) Yes — drizzle every hour, precipitation probability climbing from 76 % to 89 %.

Try it without a client

Drive the server directly over stdio with a hand-written JSON-RPC exchange:

printf '%s\n' \
  '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","clientInfo":{"name":"cli"}}}' \
  '{"jsonrpc":"2.0","method":"notifications/initialized"}' \
  '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"get_weather","arguments":{"location":"Seattle"}}}' \
  '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"get_hourly_forecast","arguments":{"location":"Tokyo","hours":6}}}' \
  | openmeteo-mcp        # or: python3 weather_mcp/server.py

The tools/call responses look like:

{"jsonrpc": "2.0", "id": 2, "result": {"content": [{"type": "text",
  "text": "Current weather in Seattle, United States:\n  Conditions:  overcast\n  Temperature: 54.2°F\n  Wind:        1.1 mph"}]}}

Hourly forecast for Tokyo, Japan (next 6 hours):
  2026-09-04 18:00  73.0°F  precip  76%  dense drizzle
  2026-09-04 19:00  72.5°F  precip  76%  dense drizzle
  2026-09-04 20:00  72.2°F  precip  78%  dense drizzle
  2026-09-04 21:00  71.8°F  precip  80%  slight rain
  2026-09-04 22:00  71.7°F  precip  84%  dense drizzle
  2026-09-04 23:00  71.3°F  precip  89%  moderate drizzle

An unknown place name comes back as a normal result with "isError": true:

{"jsonrpc": "2.0", "id": 4, "result": {"content": [{"type": "text",
  "text": "Could not find any location named 'Zzzxqq'."}], "isError": true}}

Install

Pick whichever fits your setup. All of them give you an openmeteo-mcp command (or an equivalent) that clients can launch.

The distribution is named myai-weather-mcp; both myai-weather-mcp and openmeteo-mcp launch the server.

From PyPI (after the first successful release):

pipx install myai-weather-mcp      # or: pip install myai-weather-mcp

With uv — no install step at all:

uvx myai-weather-mcp
# or straight from GitHub:
uvx --from git+https://github.com/myAI-2025/weather-mcp openmeteo-mcp

With pipx or pip:

pipx install git+https://github.com/myAI-2025/weather-mcp
# or
pip install git+https://github.com/myAI-2025/weather-mcp

From a clone (no install):

git clone https://github.com/myAI-2025/weather-mcp
python3 weather-mcp/weather_mcp/server.py     # runs the server directly

Configure a client

Claude Code

claude mcp add --scope user weather -- openmeteo-mcp

If you cloned instead of installing, point at the file:

claude mcp add --scope user weather -- python3 /path/to/weather-mcp/weather_mcp/server.py

Restart Claude Code (or reconnect via /mcp). Both tools then appear as mcp__weather__get_weather and mcp__weather__get_hourly_forecast.

Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\) and add:

{
  "mcpServers": {
    "weather": {
      "command": "openmeteo-mcp"
    }
  }
}

Using uvx instead, so nothing needs installing first:

{
  "mcpServers": {
    "weather": {
      "command": "uvx",
      "args": ["myai-weather-mcp"]
    }
  }
}

Restart Claude Desktop. The tools appear under the connectors (plug) menu.

Any other MCP client

It's a standard stdio server: launch openmeteo-mcp (or python3 -m weather_mcp) as a subprocess and speak JSON-RPC 2.0 over its stdin/stdout. See How it works below.

Development

git clone https://github.com/myAI-2025/weather-mcp
cd weather-mcp
pip install -e ".[dev]"
python3 test_server.py     # one line per check
pytest                     # same checks, pytest-style

The suite monkeypatches the network functions, so it runs offline.

How it works

weather_mcp/server.py reads newline-delimited JSON-RPC messages from stdin and writes responses to stdout:

Upstream calls: Open-Meteo geocoding (geocoding-api.open-meteo.com) then the forecast endpoint (api.open-meteo.com) with current=temperature_2m,wind_speed_10m,weather_code.

License

MIT — see LICENSE.