WikiData-MCI

!MCI Image

📖 Overview

WikiData is a vast knowledge base with over 100 million entities, making it an incredible resource for exploration and querying.

WikiData-MCI is a new-generation AI-enhanced interface to Wikidata that offers the power of large language models, agentic technology based on MCP, and user-friendly visual interactivity.

Model-Context-Interface is the user interface developed for access to a MCP server. It performs a similar role as a web browser would in interfacing with a HTTP server.

Namely, MCP servers aren't just for agents, they're also for humans. MCIs are designed to augment human intelligence and provide a user-friendly interface for accessing MCP servers. Both agents and interfaces employ LLM technology.

🌟 Features

• MCP: Model-Context-Protocol interfaces orchestrates the connection between LLM and WikiData.
• LLM: Large Language Models for enhanced querying and exploration capabilities, for example enabling automatic conversion of natural language queries into SPARQL queries and summarization of the results.
• Visualization: The structures returned by WikiData are rendered as interactive knowledge graphs, allowing additional information to be expanded into, and providing a visual representation of the relationships between entities.
• Interactivity: Providing a real-time feedback loop giving insight into the working of the agentic knowledge exploration process.

🚀 Getting Started

Prerequisites

List the software, libraries, and tools that need to be installed. For example:

- Node.js v14+
- npm or yarn
- MongoDB

Installation

Step-by-step instructions on how to install and setup your project:

1. Clone the repository

   git clone https://github.com/aleksj/wikidata-mci.git
   

2. Navigate to the project directory

   cd wikidata-mci
   

3. Install dependencies

   npm install
   

4. Configure the application

   cp .env.example .env
   

   Then edit .env with your specific configuration.

5. Start the application

   npm start
   

💻 Usage

Provide instructions and examples for use. Include screenshots as needed.

# Example code or command

📚 Documentation

For more detailed documentation, please refer to the Wiki or Docs.

🤝 Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👏 Acknowledgments

• List any collaborators, resources, or inspirations
• Anyone who helped with the project
• Inspirations

📞 Contact

Aleks Jakulin - @aleksj - aleks+mci@data.flowers

Project Link: https://github.com/aleksj/wikidata-mci