About MCP (Model Context Protocol) Frontend
MCP Frontend is the React and TypeScript user interface for the mcp-kit project. It provides a chat interface for LLMs that uses tools exposed by an MCP backend. The README states the project is under active development and not yet recommended for production.
Key features
- 01Single page application architecture
- 02Real-time chat interface with LLMs
- 03Tool-based interaction through the backend
- 04Configurable backend API endpoint
- 05Tailwind CSS styled interface
Use cases
- 01Chatting with an LLM while calling MCP tools in a browser
- 02Providing a web frontend for the mcp-kit backend
- 03Running the chat frontend from a Docker image
MCP support
The client connects to the MCP Kit backend through the API endpoint set in VITE_MCP_BACKEND_API_ENDPOINT, and the backend supplies the tool capabilities.
Details
From the project READMEMCP (Model Context Protocol) Frontend
A frontend application for the Model Context Protocol (MCP) Kit that enables enhanced interactions with Large Language Models through tool-based capabilities.
This repository is part of mcp-kit and serves as the user interface layer built with modern web technologies.
🚀 Features
- Single Page Application architecture
- Real-time chat interface with LLMs
- Tool-based interaction capabilities
- Integration with MCP backend server
- Modern, responsive UI built with React and TypeScript
🎥 Demo
Experience MCP Kit in action - chat with LLMs while leveraging additional capabilities provided by the MCP server:
🛠️ Prerequisites
- Node.js 20.x
- NPM 7.x
📦 Installation
Standard Installation
- Clone the repository:
git clone https://github.com/shaharia-lab/mcp-frontend.git
cd mcp-frontend
[Rest of standard installation steps...]
🐳 Docker Installation
You can run MCP Frontend using our official Docker image:
docker pull ghcr.io/shaharia-lab/mcp-frontend:<version>
Replace <version> with the specific version you want to use (e.g., latest, 1.0.0).
Running with Docker
docker run
-p 3000:3000
-e VITE_MCP_BACKEND_API_ENDPOINT=http://localhost:8081
ghcr.io/shaharia-lab/mcp-frontend:
Environment Variables
The following environment variables are required to run MCP Frontend:
| env_key | Default | Required | Description |
|---|---|---|---|
VITE_MCP_BACKEND_API_ENDPOINT | - | Yes | The base URL for the MCP backend API. |
Simply copy the .env.example file to .env and update the values as needed to run the application locally.
And for Docker, you can pass the environment variables using the -e flag.
🚀 Usage
Development
Run the development server:
npm run dev
Production
Build for production:
npm run build
For detailed configuration options, refer to the Vite documentation.
🏗️ Architecture
MCP Frontend is built with:
- Vite - Build tool and development server
- React - UI framework
- TypeScript - Type-safe JavaScript
- Tailwind CSS - Utility-first CSS framework
🤝 Contributing
We welcome contributions! Here's how you can help:
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Please ensure your PRs follow our coding standards and include appropriate tests.
🔍 Related Projects
- MCP-Kit Backend - The main backend server
- Documentation - Full project documentation
⚠️ Current Status
This project is under active development. While functional, it's not yet recommended for production use. We're working on:
- Enhanced error handling
- Improved performance
- Additional tool integrations
- Comprehensive testing suite
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
🤔 Support
- 📧 Email: [email protected]
- 🐛 Issue Tracker
- 💬 Discord invite: Community Chat
🙏 Acknowledgments
- The MCP Kit community
- All our contributors and supporters
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.