Understanding the Model Context Protocol (MCP) and how to use it in Claude Code. Use when user asks about MCP, Model Context Protocol, connecting external tools, MCP servers, or extending Claude's capabilities.
Connects external tools and data sources to Claude Code using the Model Context Protocol. Automatically triggered when you ask about MCP, need to extend Claude's capabilities, or want to integrate external APIs and services.
/plugin marketplace add reggiechan74/claude-plugins/plugin install claude-code-metaskill@claude-pluginsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.
MCP enables developers to connect AI models to custom tools and data sources in a standardized, interoperable manner—addressing a key need in extending Claude's capabilities beyond its base training.
The protocol integrates across multiple Anthropic offerings:
For protocol details, server/client development guidance, and community-created implementations, refer to the official MCP Documentation at modelcontextprotocol.io.
MCP tools follow the pattern: mcp__<server>__<tool>
Configure MCP tools with regex matchers in hooks:
{
"matcher": "mcp__memory__.*",
"hooks": [{"type": "command", "command": "validate.py"}]
}
MCP servers expose prompts as commands with the pattern:
/mcp__<server-name>__<prompt-name> [arguments]
These are dynamically discovered from connected MCP servers and automatically available when the server is active.
Use the /mcp built-in command to manage MCP server connections.
Plugins can include MCP servers via .mcp.json configuration for external tool integration.
Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
Implement GDPR-compliant data handling with consent management, data subject rights, and privacy by design. Use when building systems that process EU personal data, implementing privacy controls, or conducting GDPR compliance reviews.