MCPMathServer
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCPMathServerwhat is 15 times 4?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCPMathServer
A Model Context Protocol (MCP) server exposing math and weather tools, with a LangChain agent client powered by Groq.
Features
Math tools —
add,subtract,multiplyvia MCP stdio transportWeather tool —
get_weathervia MCP streamable HTTP transport (placeholder)Agent client — LangChain agent that connects to both MCP servers and answers natural-language queries using
ChatGroq
Related MCP server: SampleMCP
Prerequisites
Python 3.12+
Setup
# Clone and enter the project
git clone <repo-url> && cd MCPMathServer
# Install dependencies with uv (virtual environment is created automatically)
uv init
# For virtual environment:
uv venvCreate a .env file in the project root:
GROQ_API_KEY=your_groq_api_key_hereUsage
Run the math server (stdio)
python mathserver.pyRun the weather server (streamable HTTP)
python weather.pyRun the agent client
python client.pyThe client connects to both servers, then sends example queries:
"what's (3 + 5) x 12?"— routed to the math server"what is the weather in California?"— routed to the weather server
Project Structure
MCPMathServer/
├── mathserver.py # MCP math tool server (stdio)
├── weather.py # MCP weather tool server (streamable HTTP)
├── client.py # LangChain agent client
├── main.py # Entry point placeholder
├── pyproject.toml # Project metadata & dependencies
├── requirements.txt # Pip dependencies
└── .env # API keys (not committed)Dependencies
FastMCP — MCP server framework
LangChain — Agent framework
LangChain Groq — Groq LLM integration
LangChain MCP Adapters — MCP transport adapters
LangGraph — Agent orchestration
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