What is MCP?
MCP (Model Context Protocol) is designed to facilitate communication between language models and tool providers, enabling powerful AI-based applications.
@mkcod
基本情報
概要はまだありません
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"mcp_server_client_tutorial_using_python": {
"command": "uvx",
"args": [
"create-mcp-server"
]
}
}
}ツール一覧はまだありません
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This comprehensive guide walks you through creating both a Model Context Protocol (MCP) server and a client with a graphical user interface using Python. MCP facilitates communication between language models and tool providers, enabling AI-based applications. It is intended for developers with basic Python and async programming knowledge.
Follow the guide sequentially: set up the environment with pip install uv, create a server project using uvx create-mcp-server, implement server logic in server.py, then build a client with uv init mcp-client, add packages (mcp, anthropic, python-dotenv), and finally add a Tkinter UI via client_ui.py. Run the server with python -m server_project_name.server and the client with asyncio.run(main()).
uv.MCP (Model Context Protocol) is designed to facilitate communication between language models and tool providers, enabling powerful AI-based applications.
A Windows or Mac computer with the latest Python, familiarity with Python programming, basic understanding of async programming, and knowledge of UI concepts.
Install the `uv` tool with `pip install uv`. Then use `uv sync --dev --all-extras` for the server project and `uv add mcp anthropic python-dotenv` for the client.
Run `python -m server_project_name.server` from the server project directory. The server runs on localhost at port 8000 by default.
Install Tkinter with `uv add tk`, then create a `client_ui.py` file that imports the `MCPClient` class and builds a Tkinter interface for connection and tool calling.

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