MCP Implementation Guide

Model Context Protocol (MCP) servers extend AI capabilities by connecting to external tools, databases, and services. This guide covers setting up MCP servers in popular development environments.

Before starting, ensure you have:

• Node.js 18+ (for npx-based servers) or Docker installed
• An AI assistant that supports MCP (VS Code with GitHub Copilot, Claude Code CLI, Cursor, Windsurf)
• Basic familiarity with JSON configuration files

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Visual Studio Code Integration

VS Code

Visual Studio Code provides excellent support for MCP through its extensions and built-in capabilities starting from version 1.99. With VS Code, you can:

• Develop and test MCP servers directly in your editor
• Debug MCP server implementations
• Use integrated tools for testing MCP endpoints
• Benefit from TypeScript/JavaScript intelligence for MCP development

Key features:

• .vscode/mcp.json configuration file for project-level MCP server definitions
• User settings for global MCP server configurations
• Automatic discovery of MCP servers defined in your workspace
• Prompt suggestions based on available MCP tools

For detailed instructions on setting up and using MCP with VS Code, see our VS Code Guide.

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Claude Code CLI Integration

Claude Code

Claude Code provides first-class MCP support through its command-line interface. You can configure MCP servers in your claude.json configuration file:

• Define servers in project-level configuration
• Connect to databases, APIs, and file systems
• Use MCP tools directly from Claude Code's chat interface
• Chain multiple MCP servers for complex workflows

Key features:

• JSON configuration in claude.json for defining MCP servers
• Environment variable support for sensitive credentials
• Multi-server chaining for combining capabilities
• Real-time tool discovery as servers are added

For detailed instructions, see our Claude Code Guide.

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Choosing Your Environment

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Quick Start

1. Pick an environment from the guides above based on your workflow
2. Choose MCP servers from our MCP Servers directory that match your tools
3. Configure by copying the JSON configuration from each server's page
4. Test by asking your AI assistant to use one of the server's tools
5. Iterate by chaining multiple servers for complex workflows