infomentor_mcp

villaume/infomentor_mcp

3.2

If you are the rightful owner of infomentor_mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

Infomentor MCP server is designed to streamline administrative tasks by leveraging the capabilities of Language Learning Models (LLMs) and intelligent agents.

infomentor_mcp

Infomentor MCP server - An attempt to offload admin things to LLMs/Agents

Installation

Install dependencies using uv:

uv sync

This will create a virtual environment and install all required packages from pyproject.toml and uv.lock.

Setup Environment Variables

Create a .env file in the project root with your Infomentor credentials:

INFOMENTOR_USERNAME=your_username
INFOMENTOR_PASSWORD=your_password
INFOMENTOR_GROUP_1_ID=your_group_1_id
INFOMENTOR_GROUP_2_ID=your_group_2_id
INFOMENTOR_PUPIL_1_ID=your_pupil_1_id
INFOMENTOR_PUPIL_2_ID=your_pupil_2_id

Finding the IDs: Go to Infomentor on your computer - In the developer view > Javascript console check for the Ids:

Pupil IDs: Pupil IDs

Group IDs: Group IDs

Running the server

  1. Start the MCP server:
uv run python main.py
  1. In another terminal, expose it with ngrok:
ngrok http 8000
  1. Copy the ngrok URL from the output (e.g., https://xxxx-xxxx.ngrok-free.app)

Testing with MCP Inspector

  1. Start the inspector:
npx @modelcontextprotocol/inspector
  1. Connect using: https://YOUR-NGROK-URL.ngrok-free.app/sse
    • Protocol: Select "SSE" in the dropdown
    • Note: Use the /sse path (this is the SSE endpoint)
    • Make sure to use the current ngrok URL each time (they change on restart)

Using the MCP server

Inspector

In claude for instance: Claude