What is Mcp Server

MCP_Server is a Machine Context Protocol server implementation that enables AI assistants to interact with custom tools and resources. It is built using the @modelcontextprotocol/sdk package and offers a modular architecture for extending capabilities.

Use cases

Use cases for MCP_Server include developing custom AI tools for code assistance, automating repetitive tasks in development, and enhancing the capabilities of AI assistants in various programming environments.

How to use

To use MCP_Server, install the dependencies using ‘pnpm install’, build the project with ‘pnpm run build’, and start the server using ‘pnpm start’. For integration with VS Code, configure the server in the .vscode/mcp.json file and enable automatic discovery in settings.json.

Key features

Key features of MCP_Server include a modular architecture for organizing tools and resources, stdio communication for compatibility with VS Code, environment variable management using dotenv, and support for TypeScript.

Where to use

MCP_Server can be used in software development environments, particularly where AI assistants are integrated into workflows to enhance productivity and tool interaction.

MCP

Machine Context Protocol (MCP) server.

Overview

This is a Model Context Protocol (MCP) server implementation that allows AI assistants like Claude to interact with your custom tools and resources. The server is built using the official @modelcontextprotocol/sdk package and provides a modular architecture for adding custom capabilities.

This MCP server runs as a Node.js application and communicates over stdio, making it compatible with VS Code’s MCP integration. It’s designed to be extensible, allowing you to add custom tools, resources, and prompts to enhance AI capabilities in your development workflow.

Installation

# Install dependencies
pnpm install

# Build the project
pnpm run build

# Start the server
pnpm start

Configuration for VS Code

To use this MCP server with VS Code, add the following to your .vscode/mcp.json file (or move it to settings.json for global usage):

{
  "servers": {
    "my-mcp-server": {
      "command": "node",
      "args": [
        "/absolute/path/to/mcp/dist/index.js"
      ],
      "env": {}
    }
  }
}

Make sure to replace /absolute/path/to with the actual absolute path to the mcp directory.

Additionally, ensure that automatic discovery is enabled in your settings.json file:

{
  "chat.mcp.discovery.enabled": true
}

You can also verify the discovery and configuration by using the command palette in VS Code:

1. Press Ctrl + Shift + P (or Cmd + Shift + P on macOS).
2. Search for MCP.
3. Use the available options to check the discovery and configuration settings.

Features

This MCP server provides a structured foundation for building custom tools and capabilities for AI assistants with:

• Modular Architecture: Organized into distinct modules for tools, resources, and prompts
• Stdio Communication: Compatible with VS Code’s MCP integration through stdio transport
• Environment Configuration: Uses dotenv for environment variable management
• TypeScript Support: Full TypeScript integration for type safety
• Extensible Design: Easily add new tools and capabilities by implementing the provided interfaces

The server is designed to be expanded with custom tools for helping with components, layouts, and documentation as indicated in the capabilities description.

Project Structure

mcp/
├── src/
│   ├── index.ts              # Main entry point, server initialization
│   ├── prompts/              # Prompt registration and management
│   │   └── index.ts          # Prompt registration module
│   ├── resources/            # Resource definitions and handlers
│   │   └── index.ts          # Resource registration module
│   └── tools/                # Tool implementations
│       └── index.ts          # Tool registration module
├── .github/                  # GitHub-specific files
│   └── FUNDING.yml           # Sponsorship configuration
├── eslint.config.js          # ESLint configuration
├── package.json              # Project metadata and dependencies
├── pnpm-lock.yaml            # Dependency lock file
├── tsconfig.json             # TypeScript configuration
└── README.md                 # Project documentation

Development

To add new features or extend existing ones:

1. Add or update service methods in the appropriate service file.
2. Register the tool in the corresponding tools file.
3. Build and test your changes.

MCP SDK Integration

This project uses the @modelcontextprotocol/sdk package to create a Machine Context Protocol server that Claude can interact with. The MCP architecture enables Claude to:

• Call specific tools defined in the server
• Receive structured responses
• Provide a better experience for related inquiries

The implementation follows the standard MCP patterns with:

• Server initialization using McpServer
• StdioServerTransport for communication

License

MIT