MCP Jo1

🚀 MCP Personal Server and Client for LLM

The MCP personal server and client are designed to work with Large Language Models (LLMs), providing a platform for weather - related data acquisition and interaction.

🚀 Quick Start

Project Initialization

1. Initialize a new project using uv

uv init --python=3.10 .
touch .gitignore .env
cat << EOF >> .gitignore
.env
.venv/
__pycache__/
EOF

2. Create a Python virtual environment

uv venv
source .venv/bin/activate

3. Install dependencies

uv add dashscope httpx mcp python-dotenv langchain langchain-core langchain-mcp-adapters langchain-community langgraph

✨ Features

MCP Server

Weather Service MCP Server

This is a weather service MCP server for obtaining weather data in the United States.

Create a Project

# Create a new directory
mkdir -p servers/weather-server-mcp

# Create a virtual environment and activate it
uv venv
source .venv/bin/activate

# Create our server file
cd servers/weather-server-mcp
touch weather.py

Run the Server

1. Copy the server configuration file from the MCP host (e.g., OpenCat)
2. Select the tool (weather) for this MCP server
3. Chat in the host (e.g., OpenCat)

MCP Client

Weather Server MCP Client

This is a weather service MCP client for obtaining weather data in the United States.

Create a Project

# Create the project directory
mkdir -p clients/mcp-client

# Create a virtual environment
uv venv
# Activate the virtual environment
source .venv/bin/activate

# Create our main file
cd clients/mcp-client
touch client.py

Run the Client

# Run the client with the weather mcp server as the backend
uv run ./clients/mcp-client/client.py ./servers/weather-server-mcp/weather.py

Check the MCP Server

npx @modelcontextprotocol/inspector \
  uv \
  --directory servers/weather-server-mcp \
  run \
  weather.py