epic-mcp

An Epic Stack example adding support for the Model Context Protocol (MCP).

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools.

Learn more from the MCP Documentation

This repository demonstrates how to integrate MCP into an Epic Stack application. The implementation includes:

1. Server-side MCP setup for handling client connections
2. SSE (Server-Sent Events) transport layer for real-time communication
3. Example tool implementations showing how to expose functionality to LLMs

export const server = new McpServer(
	{
		name: 'epic-mcp-a25d',
		version: '1.0.0',
	},
	{
		capabilities: {
			tools: {},
		},
	},
)

The MCP server is the core component that handles tool registration and execution. It's configured with a unique name and version, and defines the capabilities it provides.

server.tool(
	'Find User',
	'Search for users in the Epic Notes database by their name or username',
	{ query: z.string().describe('The query to search for') },
	async ({ query }) => {
		// Implementation...
	},
)

Tools are the primary way to expose functionality to LLMs. Each tool:

• Has a descriptive name and purpose
• Uses Zod for type-safe parameter validation
• Can return multiple content types (text, images, etc.)
• Integrates with your existing application logic

The transport layer handles the bi-directional communication between the MCP client and server:

• Uses Server-Sent Events (SSE) for real-time server-to-client communication
• Handles POST requests for client-to-server messages
• Maintains session state for multiple concurrent connections

export async function loader({ request }: Route.LoaderArgs) {
	const url = new URL(request.url)
	const sessionId = url.searchParams.get('sessionId')
	const transport = await connect(sessionId)
	return transport.handleSSERequest(request)
}

The Remix route:

• Establishes SSE connections for real-time communication
• Handles incoming tool requests via POST endpoints
• Manages session state for multiple clients

1. Tool Design: When designing tools for LLMs:

   • Provide clear, descriptive names and purposes
   • Use strong type validation for parameters
   • Return structured responses that LLMs can understand
   • Consider supporting multiple content types (text, images, etc.)

2. State Management: The implementation demonstrates:

   • Session-based connection tracking
   • Clean connection cleanup on client disconnect
   • Safe concurrent client handling

3. Integration Patterns: Learn how to:

   • Connect MCP with existing application logic
   • Handle real-time communication in Remix
   • Structure your MCP implementation for maintainability

4. Security Considerations:

   • Session-based access control
   • Safe handling of client connections
   • Proper cleanup of resources