weather-mcp-a2a
Verified Safeby manuelalba1021
Overview
An agentic AI system that fetches and reasons over real-time global weather data using the Model Context Protocol (MCP) and large language models.
Installation
streamlit run Weather_streamlit_app.pyEnvironment Variables
- GROQ_API_KEY
Security Notes
The project adheres to good security practices by loading API keys from environment variables (`.env`). External API calls are made using `httpx` and `requests` to well-known weather APIs (`api.weather.gov`, `open-meteo.com`), which mitigates direct network risks. Input sanitization for city names used in API requests relies on URL parameter encoding by the `requests` library, which is generally robust against injection. No use of `eval` or other dangerous code execution patterns was identified. The most significant concern, noted in the project's internal documentation, is the unreliability of certain LLMs (Groq models) in correctly formatting tool calls, which led to a direct API implementation workaround in the main Streamlit app. This workaround itself is implemented securely, but deviates from the intended agentic workflow.
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