MCP Server for ML Model Integration
Integrations
Integrates with a FastAPI hosted ML server to serve a trained Random Forest model for predictions and data processing.
Provides integration with GitHub repositories for cloning and accessing code resources needed for the MCP server setup.
Integrates with Imgur for image hosting used in the demonstration of the MCP server capabilities.
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 šŗ
Startup MCP Server š
- Clone this repo
git clone https://github.com/nicknochnack/BuildMCPServer - To run the MCP server
cd BuildMCPServeruv venvsource .venv/bin/activateuv add .uv add ".[dev]"uv run mcp dev server.py - To run the agent, in a separate terminal, run:
source .venv/bin/activateuv run singleflowagent.py
Startup FastAPI Hosted ML Server
git clone https://github.com/nicknochnack/CodeThat-FastMLcd CodeThat-FastMLpip install -r requirements.txtuvicorn mlapi:app --reload
Detailed instructions on how to build it can also be found here
Other References š
- Building MCP Clients (used in singleflow agent)
- Original Video where I build the ML server
Who, When, Why?
šØš¾āš» Author: Nick Renotte š Version: 1.x š License: This project is licensed under the MIT License
This server cannot be installed
A server that integrates trained Random Forest models with Bee Framework, enabling ReAct interactivity for AI tools and agents.