end2end-mcp

# end2end-mcp An end-to-end example of building Model Context Protocol (MCP) clients and communicates between several MCP servers with OpenAI compatible APIs.  ## TL;DR You can run your MCP servers with a similar method as you run them with Claude Desktop App for just a simple command: ```bash uv run python client/client.py ``` ## Prerequisites 1. Make sure you have `uv` installed. ```bash uv venv source .venv/bin/activate uv sync ``` ## Brief Introduction ### Example MCP servers 1. Shioaji: An example MCP server that provides basic stock trading functionalities using [Shioaji API](https://sinotrade.github.io/), you'll need further configuration to properly use it. 2. Weather: Just a simple example from [MCP official doc](https://modelcontextprotocol.io/quickstart/server) ### MCP host Instead of following the Claude API, I replace it with OpenAI compatible APIs, supporting two main LLM providers: 1. OpenAI 2. Ollama Where you can change between them by modifying the `LLM_PROVIDER` environment variable. ### Connect with MCP host After choosing your LLM provider, you can connect servers with the MCP host by modifying the `config.json` file, just like the example below: ```json { "mcpServers": { "weather": { "args": [ "--directory", "root_path", "run", "server_file.py" ], "command": "uv_exec_command" } } } ``` ### Run MCP host You can run the MCP host with the following command: ```bash uv run python client/client.py ``` After finishing playing with the MCP host, you can just type `exit` to leave > The **shioaji-server** in `server/` is certified by MCP Review. The [mcp review link](https://mcpreview.com/mcp-servers/AbnerTeng/shioaji-mcp)