Gauntlet Incept

by birdsmith

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GitHub

About

Integrates with QTI services and LLMs to generate personalized educational content tailored to students' knowledge levels and interests, streamlining the creation of adaptive learning materials.

Details

Author: birdsmith
Repository: Birdsmith/Gauntlet-Incept-MCP
GitHub stars: 1
Categories: AI, Design, File Management, Database, Knowledge Base, Developer Tools, Infrastructure

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:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below
Plugin Name Gauntlet Incept

Command (node, npx, python, etc.) npx
Arguments
- Argument 1 -y
- Argument 2 @highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

From the repository

1. Clone the repository

   git clone https://github.com/yourusername/Gauntlet-Incept.git

2. Navigate to the project directory

   cd Gauntlet-Incept

3. Install dependencies

   npm install

4. Copy the example environment file and update it with your values

   cp .env.example .env

5. Run the project

   npm start

1. Build and start the containers

   docker-compose up -d

2. Access the API at http://localhost:3000
3. Access the MCP server at http://localhost:3001

`tag_question`

Tag a question with subject, grade, standard, lesson, and difficulty. Endpoint: POST /api/question/tag

`grade_question`

Grade a tagged question against quality standards. Endpoint: POST /api/question/grade

`generate_question`

Generate a question based on tags or an example question. Endpoint: POST /api/question/generate

`tag_article`

Tag an article with subject, grade, standard, and lesson. Endpoint: POST /api/article/tag

`grade_article`

Grade a tagged article against quality standards. Endpoint: POST /api/article/grade

`generate_article`

Generate an article based on tags or an example article. Endpoint: POST /api/article/generate

Claude Desktop / Cursor

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

{
    "mcpServers": {
        "gauntlet incept": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Linux

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Macos

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Windows

{
    "env": [],
    "args": [
        "/c",
        "npx",
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "cmd"
}

Gauntlet-Incept

A system for generating high-quality educational content tailored to students' knowledge levels and interests.

Project Description

This repository contains the code and resources for the Gauntlet-Incept project, which aims to build a system that generates high-quality educational content for K-8 students. The initial scope focuses on developing educational content in the form of articles and question banks for specific subject areas.

Documentation

- Project Overview - Detailed description of the project goals and requirements
- Implementation Checklist - Comprehensive checklist for project implementation
- Original Project Brief - Original project brief with detailed requirements
- MCP Server Guide - Guide for using the Model Context Protocol server with Claude Desktop

Project Structure

gauntlet-incept/
├── docs/                  # Documentation files
├── src/                   # Source code
│   ├── api/               # API routes
│   ├── models/            # Data models
│   ├── services/          # Business logic
│   ├── utils/             # Utility functions
│   ├── data/              # Data files
│   ├── tests/             # Test files
│   ├── index.js           # Entry point for REST API
│   └── mcp-server.js      # Model Context Protocol server
├── services/              # Microservices
│   ├── qti-service/       # QTI service for content storage
│   └── llm-service/       # LLM service for content generation
├── .env.example           # Example environment variables
├── .gitignore             # Git ignore file
├── package.json           # Node.js package file
├── docker-compose.yml     # Docker Compose configuration
├── Dockerfile             # Docker configuration
└── README.md              # This file

API Endpoints

The project implements six core API endpoints:

Question Endpoints

- POST /api/question/tag - Tag a question with subject, grade, standard, lesson, and difficulty
- POST /api/question/grade - Grade a tagged question against quality standards
- POST /api/question/generate - Generate a question based on tags or an example question

Article Endpoints

- POST /api/article/tag - Tag an article with subject, grade, standard, and lesson
- POST /api/article/grade - Grade a tagged article against quality standards
- POST /api/article/generate - Generate an article based on tags or an example article

Model Context Protocol (MCP) Server

In addition to the REST API, this project includes an MCP server that allows Claude Desktop to interact with the Gauntlet Incept system. This enables Claude to generate, tag, and grade educational content directly.

See the MCP Server Guide for details on how to set up and use the MCP server with Claude Desktop.

Getting Started

Prerequisites

- Git
- Node.js (v14 or higher)
- Access to the RDS PostgreSQL database (credentials provided by administrator)
- SSH key for database connection (if connecting through SSH tunnel)
- Docker and Docker Compose (optional, for containerized deployment)

Installation

1. Clone the repository

   git clone https://github.com/yourusername/Gauntlet-Incept.git

2. Navigate to the project directory

   cd Gauntlet-Incept

3. Install dependencies

   npm install

4. Copy the example environment file and update it with your values

   cp .env.example .env

5. Run the project

   npm start

Running with Docker

1. Build and start the containers

   docker-compose up -d

2. Access the API at http://localhost:3000
3. Access the MCP server at http://localhost:3001

Database Connection

This project connects to an Amazon RDS PostgreSQL instance with the following details:

- Host: alphacommoncrawl-core-reboot.cluster-caeuiwckzo1a.us-east-1.rds.amazonaws.com
- Port: 5432
- Database: core
- Username: postgres

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About

Details

Jump to

Setting up with Highlight

From the repository

tag_question

grade_question

generate_question

tag_article

grade_article

generate_article

Claude Desktop / Cursor

Linux

Macos

Windows

Gauntlet-Incept

Project Description

Documentation

Project Structure

API Endpoints

Question Endpoints

Article Endpoints

Model Context Protocol (MCP) Server

Getting Started

Prerequisites

Installation

Running with Docker

Database Connection

Install

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Activepieces

`tag_question`

`grade_question`

`generate_question`

`tag_article`

`grade_article`

`generate_article`