1. Conduid
  2. Agents
  3. Palette
MCP server · Agents

Palette

Desktop application for managing Model Context Protocol servers (MCP). Provides a centralized interface to configure and manage MCP servers for use with LLMs and AI assistants such as Claude.

34Low

Scored 6 days ago · breakdown

About Palette

Palette is an MCP server in the Agents category: desktop application for managing Model Context Protocol servers (MCP). Provides a centralized interface to configure and manage MCP servers for use with LLMs and AI assistants such as Claude.

The repository has 4 stars and 0 forks.

Install

From source
git clone https://github.com/cellwebb/mcp-palette

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

✦

Ask AI about Palette

Powered by Claude · Grounded in docs

I know everything about Palette. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

  • ✓README presentThe repository ships documentation.

5 checks have not been run yet.

README

MCP Palette: Model Context Protocol Server Manager

Build Status Coverage Status npm version

MCP Palette is a modern, user-friendly desktop application for managing Model Context Protocol (MCP) server configurations. It provides a centralized interface to configure, manage, and deploy MCP servers for use with Large Language Models (LLMs) and AI assistants.

🚀 Features

  • Profile Management: Create, edit, rename, and organize server configurations in profiles
  • Server Master List: Maintain a reusable library of server configurations
  • Profile-Specific Overrides: Customize servers for specific profiles without duplicating configuration
  • Enable/Disable Servers: Temporarily disable servers while preserving customizations
  • JSON Editing: Direct editing of configuration files for advanced users
  • Import/Export: Share configurations between teams and environments
  • UI Optimizations: Keyboard support for common operations (Enter to save, Escape to cancel)

🔧 Use Cases

  • Configure local development environments for AI agents
  • Maintain different server setups for various projects
  • Set up standardized server configurations for team members
  • Create specialized profiles for different AI assistant use cases
  • Deploy consistent MCP server configurations in production environments

🖥️ Installation & Usage

For End Users

  1. Download the installer from the Releases page.
  2. Run the installer for your OS.
  3. Launch MCP Palette from your Applications folder or Start Menu.

See the Usage Guide for feature explanations.

For Developers

  1. Clone the repo and install dependencies:
    git clone https://github.com/cellwebb/mcp-palette.git
    cd mcp-palette
    npm install
    
  2. Run in development mode:
    npm run electron:dev
    
  3. Build a distributable version:
    npm run electron:build
    

Cross-platform builds:
If you need a Windows or Linux installer and are on a Mac, use GitHub Actions or a Windows/Linux machine.


📚 Documentation

🏗️ Development

This project uses Vite (frontend) and Electron (desktop wrapper). See Architecture Overview for project structure.

Note for Contributors:
See CONTRIBUTING.md for dev instructions, including React DevTools usage.


🤖 Continuous Integration

  • CI/CD powered by GitHub Actions.
  • Tests and coverage run on each push/PR to main.
  • See Electron Builder docs for cross-platform build automation.

📁 Project Structure

mcp-palette/
├── electron/                  # Electron-specific code
│   ├── main.js                # Main process entry
│   ├── preload.js             # Preload script
│   └── store.js               # Data storage management
├── public/                    # Static assets
├── src/                       # Frontend React code
│   ├── App.jsx                # Main React component
│   ├── components/            # React components
│   │   ├── ProfileSelector.jsx
│   │   ├── ServerMasterList.jsx
│   │   └── ...
│   ├── styles/                # CSS styles
│   ├── utils/                 # Utility functions
│   │   └── profileUtils.js
│   └── main.jsx               # Frontend entry point
├── package.json
└── vite.config.js             # Vite configuration

🤝 Contributing

Contributions are welcome! Feel free to submit issues or pull requests.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📝 License

MIT License

See LICENSE for details.

📚 Related Projects

📊 What is MCP?

The Model Context Protocol (MCP) is a standardized protocol for enabling Large Language Models (LLMs) like Claude to access external tools, data sources, and APIs. MCP allows AI assistants to interact with the outside world, enhancing their capabilities with real-time data access, computations, and external services.

MCP Palette helps developers and teams manage the server configurations needed to enable these extended capabilities in a consistent, organized way.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Palette

How do I install Palette?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Palette safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Palette still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.