Quizzard

by hrmtsh2

212 downloads
Not rated
GitHub

About

Quizzard is an MCP server for trivia and quizzing enthusiasts. Includes multiple popular quizzing sources (Open Trivia Database, J! Archive for Jeopardy! questions), and ability for users to upload PDFs and link to websites of their own choosing. Features include - progress track

Details

Author
hrmtsh2
Downloads
212
Categories
Other

- Integrates with Open Trivia Database and J! Archive.
- Supports uploading PDFs and linking websites for custom content.
- Tracks quiz progress and logs each session.
- Detects weak areas in user knowledge.
- Provides personalised recommendations.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Quizzard
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "quizzard": {
            "quizzard": {
                "command": "python",
                "args": [
                    "path/to/quizzard/server.py"
                ]
            }
        }
    }
}

McpServers

{
    "quizzard": {
        "command": "python",
        "args": [
            "path/to/quizzard/server.py"
        ]
    }
}

Quizzard is an MCP server for trivia and quizzing enthusiasts. Includes multiple popular quizzing sources (Open Trivia Database, J! Archive for Jeopardy! questions), and ability for users to upload PDFs and link to websites of their own choosing. Features include - progress tracking and session-wise logging, weak area detection, personalised recommendations, among others (see README.md on linked GitHub page)

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