santosh-ksharma/mcp-weather
3.2
If you are the rightful owner of mcp-weather and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to dayong@mcphub.com.
The Model Context Protocol (MCP) server facilitates seamless integration between language models and external data sources or services, enabling dynamic and context-aware interactions.
Tools
1
Resources
0
Prompts
0
How the LLM Uses These Tools
Example 1: Weather Alerts
You: "Are there any weather alerts in California?"
Claude's process:
- Recognizes it needs weather alert info
- Calls
get_alerts(state="CA") - Gets the formatted response
- Presents it to you in natural language
Example 2: Weather Forecast
You: "What's the weather forecast for San Francisco?"
Claude's process:
- Knows SF coordinates (or looks them up)
- Calls
get_forecast(latitude=37.7749, longitude=-122.4194) - Gets 5-period forecast
- Summarizes it for you
Run the mcp server
uv run weather.py
Update the claude config file claude_desktop_config.json to below content
{ "mcpServers": { "weather": { "command": "/Users/santhosh.sharma/.local/bin/uv", "args": [ "--directory", "/Users/santhosh.sharma/Repositories/mcp-weather", "run", "weather.py" ] } } }
Reference : https://modelcontextprotocol.io/docs/develop/build-server#python
Analyze logs in ~/Library/Logs/Claude/mcp.log
When you ask Claude (with this MCP server connected):
Docstring best practises:
- First line = One-line summary (imperative mood: "Get", "Format", "Calculate")
- Use present tense ("Returns the sum" not "Will return")
- Be specific about parameter types and expected values
- Include examples for complex functions
- Keep it updated when code changes