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MCP Server for ML Model Integration

by nicknochnack
GitHub
Python
13
OverviewInspectNewSchemaRelated ServersReviewsScore
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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 📺

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

This server cannot be installed

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license - not found
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A server that integrates trained Random Forest models with Bee Framework, enabling ReAct interactivity for AI tools and agents.

  1. See it live and in action 📺
    1. Startup MCP Server 🚀
      1. Startup FastAPI Hosted ML Server
        1. Other References 🔗 </br>
          1. Who, When, Why?

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