math-tutor-mcp-server

bloobglob/math-tutor-mcp-server

3.2

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The Model Context Protocol (MCP) server facilitates communication between local or remote LLM models and applications, enabling seamless integration and interaction for various use cases.

Math Tutor Agent Tutorial

🧮 Dify Math Tutor Agent Setup with Custom LLM

This guide walks you through setting up Dify, integrating a custom local LLM model, and creating a Math Tutor Agent using the Dify platform for intelligent mathematical tutoring and problem-solving assistance.

🛠️ Prerequisites

Ensure the following are available:

  • Dify (at least v1.6.0) installed and running via Docker. Do not run on localhost
  • A local or remote LLM endpoint (e.g., hosted via FastAPI)
  • Access to the LLM model llm_en_v_1_3_1 or llm_zh_v_1_3_1 (or your preferred OpenAI-compatible model)
  • Python environment with required dependencies

🚀 Step-by-Step Setup

Step 1: Add LLM Model to Dify

  1. Click the user icon in the top-right corner of the interface.
  2. Select Settings from the dropdown menu.
  3. Navigate to the Model Provider tab.
  4. Install the OpenAI-API-compatible model if not already installed.
  5. In the OpenAI-API-compatible model, click Add Model and configure:
    • Model Type: LLM
    • Model Name: llm_en_v_1_3_1 or llm_zh_v_1_3_1
    • Model display name: llm_en_v_1_3_1 or llm_zh_v_1_3_1
    • API endpoint URL: http://<your-server-ip>:5001/openai/v1
    • Model context size: 4096
    • API Key: Leave blank if not needed
  6. Mark it as default if desired.

Step 2: Set up the MCP Server

  1. Start the MCP server by navigating to this project directory and running: 
    python server.py
  2. At the top of the Dify interface, navigate to the Tool tab.
  3. Click the MCP tab.
  4. Click Add MCP Server (HTTP) and configure:
    • Server URL: http://host.docker.internal:8001/mcp/
    • Name & Icon: Math Tutor MCP Server
    • Server Identifier: math-tutor-mcp-server

Step 3: Create the MCP Agent in Dify

  1. On the main interface in Dify, click Import DSL file in the Create App block.
  2. Select Math Tutor Agent.yml in this directory.
  3. Configure the agent workflow:
    • Connect the LLM Node to use your configured model
    • If using llm_zh_v_1_3_1, update each LLM block to use this model
    • Define system prompts for mathematical tutoring and problem-solving

✅ Final Notes

  • Ensure the local LLM server is accessible to Dify.
  • The MCP server must be running before using the Math Tutor Agent.
  • Debug logs can help confirm each stage is functioning as expected.
  • Test with simple mathematical problems before attempting complex tutoring scenarios.
  • The agent supports both English (llm_en_v_1_3_1) and Chinese (llm_zh_v_1_3_1) models.

📎 Resources