Connects to the DeepSeek platform (which uses the OpenAI API format) to access LLM capabilities through the deepseek-chat model.
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., "@MCP-Weather Serverwhat's the forecast for Tokyo tomorrow?"
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.
MCP-Augmented LLM for Reaching Weather Information
Overview
This system enhances Large Language Models (LLMs) with weather data capabilities using the Model Context Protocol (MCP) framework.
Related MCP server: OpenWeatherMap MCP Server
Demo
Components
MCP Client: Store LLms
MCP Server: Intermediate agent connecting external tools / resources
Configuration
DeepSeek Platform
BASE_URL=https://api.deepseek.com
MODEL=deepseek-chat
OPENAI_API_KEY=<your_api_key_here>OpenWeather Platform
OPENWEATHER_API_BASE=https://api.openweathermap.org/data/2.5/weather
USER_AGENT=weather-app/1.0
API_KEY=<your_openweather_api_key>Installation & Execution
Initialize project:
uv init weather_mcp
cd weather_mcpwhere weather_mcp is the project file name.
Install dependencies:
uv add mcp httpxLaunch system:
cd ./utils
python client.py server.pyNote: Replace all
<your_api_key_here>placeholders with actual API keys
This server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.