#atom

Creating clients that connect to MCP servers

Core Idea: MCP clients connect to MCP servers to access tools and functionality, requiring specific implementation patterns to establish connections and handle tool calls effectively.

Key Elements

Implementation Steps

1. Client Setup

   • Import the MCP client from your AI framework (e.g., experimental_createMCPClient from Vercel AI)
   • Specify the endpoint URL for the MCP server
   • Provide a name for the service (for identification purposes)
   • Await the connection to retrieve available tools

2. Tool Integration

   • Collect tools from the MCP client using await mcpClient.tools()
   • Add these tools to your existing tools list
   • Ensure your system prompt directs the AI to use these tools when appropriate

3. Connection Handling

   • Implement proper error handling for connection issues
   • Consider connection timeouts and retry logic for production applications

Code Example

// Import the MCP client
import { experimental_createMCPClient } from 'ai';

// Create an MCP client that connects to our order service
const mcpClient = experimental_createMCPClient({
  url: 'http://localhost:881/sse', // SSE endpoint
  name: 'orderService'
});

// Get the available tools from the MCP client
export async function getTools() {
  // Get tools from the MCP client
  const mcpTools = await mcpClient.tools();
  
  // Combine with other tools if needed
  return {
    getProducts,
    recommendGuitar,
    ...mcpTools // Adds tools from MCP server
  };
}

Use Cases

• Web Applications: Connect front-end applications to MCP servers to extend AI assistant capabilities
• Business Intelligence: Use MCP clients to enable AI tools to access specialized business services
• Multi-Service Integration: Allow AI assistants to communicate with multiple backend services through MCP

Best Practices

• Properly document the tools available from the MCP server
• Provide clear instructions in system prompts about when to use specific tools
• Handle errors gracefully when MCP services are unavailable
• Consider security implications of exposing services through MCP

Additional Connections

• Broader Context: Model Context Protocol (framework these clients implement)
• Applications: AI Assistant Integration (practical applications of MCP clients)
• See Also: Tool Call Flow (process of how tools are invoked and executed)

References

1. Blue Collar Coder video on Model Context Protocol implementation
2. Vercel AI documentation for experimental MCP clients

#mcp #client #ai-tools #implementation

Connections:

Sources:

• From: Jack Herrington - Applied Model Context Protocol (MCP) In 20 Minutes