Back to MCP directory
publicPublicdnsLocal runtime

BuildMCPServer

该项目提供了一套完整的MCP服务器构建指南,用于部署训练好的随机森林模型,并与Bee框架集成实现ReAct交互功能。

article

README

🚀 构建MCP服务器

本项目主要提供了构建MCP服务器以及启动FastAPI托管的ML服务器的详细步骤,帮助开发者快速搭建相关环境。

🚀 快速开始

📦 构建MCP服务器

  1. 克隆此仓库:
git clone https://github.com/nicknochnack/BuildMCPServer
  1. 运行MCP服务器:
cd BuildMCPServer
uv venv
source .venv/bin/activate
uv add .
uv add ".[dev]"
uv run mcp dev server.py
  1. 启动代理程序,在另一个终端中运行:
source .venv/bin/activate
uv run singleflowagent.py

🚀 启动FastAPI托管的ML服务器

git clone https://github.com/nicknochnack/CodeThat-FastML
cd CodeThat-FastML
pip install -r requirements.txt
uvicorn mlapi:app --reload

📚 详细文档

有关如何构建它的详细说明,请参见 这里

🔗 其他参考资料

📄 许可证

👨🏾💻 作者:Nick Renotte
📅 版本:1.x
📜 此项目采用 MIT 许可证。

help

Runtime guide

cloud

Hosted runtime

Hosted servers run from a provider-managed environment. You usually connect the MCP client to the hosted endpoint or follow the provider's authorization flow, without keeping a local process alive

  1. Open provider connection page
  2. Authorize or copy endpoint
  3. Connect from your MCP client
terminal

Local runtime / other methods

Local servers run on your own machine or infrastructure. You normally copy the server_config into your MCP client, install the required package, and provide env variables from env_schema when needed

  1. Copy server_config
  2. Install required package
  3. Fill env variables and restart client