Build a MCP Server

Build a MCP Server

By nicknochnack GitHub

A complete walkthrough on how to build an MCP server to serve a trained Random Forest model and integrate it with Bee Framework for ReAct interactivity.

mcp ml-server
Overview

What is BuildMCPServer?

BuildMCPServer is a comprehensive guide on how to build a Machine Learning (ML) server that serves a trained Random Forest model and integrates with the Bee Framework for interactive applications.

How to use BuildMCPServer?

To use BuildMCPServer, clone the repository from GitHub, set up a virtual environment, and follow the provided commands to run the MCP server and the agent.

Key features of BuildMCPServer?

  • Step-by-step instructions for building an MCP server.
  • Integration with the Bee Framework for interactive ML applications.
  • Support for running a FastAPI hosted ML server.

Use cases of BuildMCPServer?

  1. Serving machine learning models for real-time predictions.
  2. Creating interactive applications using the Bee Framework.
  3. Educational purposes for learning about ML server deployment.

FAQ from BuildMCPServer?

  • What is the purpose of the MCP server?

The MCP server is designed to serve machine learning models and facilitate interactive applications.

  • Is there a video tutorial available?

Yes! Detailed instructions and a video tutorial are provided in the repository.

  • What programming language is used?

The project is primarily written in Python.

Content

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 🔗

Who, When, Why?

👨🏾‍💻 Author: Nick Renotte
📅 Version: 1.x
📜 License: This project is licensed under the MIT License

No tools information available.

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