A
securityF
licenseA
qualityA Model Context Protocol server that provides AI agents with tools to retrieve weather alerts and detailed forecasts for US locations using the National Weather Service API.
Last updated -
2
80
TypeScript
Manages environment variables for API keys, specifically configured to store the GROQ_API_KEY needed for the server's operation.
Enables interaction with a Math Server that performs mathematical operations and a Weather Server that provides weather information based on location codes.
I am using UV as virtual envirnoment
My client llm will call Math Server to get addition and multiplcation then it will pass the value from math Server to weather server to get the weather details.
TODOS:
- Instead of returning multiplcation - return zip code. Pass that zipcode to weather server to get the weather result.
- Please create a .env file and add GROQ_API_KEY="YOUR KEY"
Commands to Run ```uv init`` if you dont have pyproject.toml or if you are doing from scratch.
Open Terminal 1 to run weather
uv venv
source .venv/bin/activate
uv add -r requirements.txt
python weather.py
Open Terminal 2 to run client that aggregates addition and weather
uv venv
source .venv/bin/activate
uv add -r requirements.txt
python client.py or python client_local_ollama.py for local
To RUN Locally
Install Ollama. Once Ollama installed, Please verify by running
ollama run llama3 if it worked then we are good to go.
Output
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A multi-agent system that connects a math server and weather server, allowing users to perform mathematical operations and retrieve weather information based on the numerical results.
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