Shioaji-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:

uv run python client/client.py

Prerequisites

1. Make sure you have uv installed.

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, you'll need further configuration to properly use it.
2. Weather: Just a simple example from MCP official doc

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:

{
  "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:

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