19:I[968,["6874","static/chunks/6874-f5ece97ffc584dd8.js","3063","static/chunks/3063-7b7219070832f2a1.js","5631","static/chunks/app/list/page-556055edcdaf7d9a.js"],"default"] 1a:T638,# Build a MCP Server A complete walkthrough on how to build a MCP server to serve a trained Random Forest model and integrate it with Bee Framework for ReAct interactivity. ## See it live and in action 📺

# Startup MCP Server 🚀 1. Clone this repo `git clone https://github.com/nicknochnack/BuildMCPServer` 2. To run the MCP server\ `cd BuildMCPServer`\ `uv venv`\ `source .venv/bin/activate`\ `uv add .`\ `uv add ".[dev]"`\ `uv run mcp dev server.py` 3. To run the agent, in a separate terminal, run:\ `source .venv/bin/activate`\ `uv run singleflowagent.py` # Startup FastAPI Hosted ML Server `git clone https://github.com/nicknochnack/CodeThat-FastML`\ `cd CodeThat-FastML`\ `pip install -r requirements.txt`\ `uvicorn mlapi:app --reload`\ Detailed instructions on how to build it can also be found here
# Other References 🔗
- Building MCP Clients (used in singleflow agent)
- Original Video where I build the ML server # Who, When, Why? 👨🏾‍💻 Author: Nick Renotte
📅 Version: 1.x
📜 License: This project is licensed under the MIT License