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