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Core component for exposing tools and resources to LLM applications

Core Idea: In Model Context Protocol (MCP), servers are specialized components that expose tools, resources, and prompts to host applications, enabling LLMs to access external functionality through a standardized interface.

Key Elements

Core Functions

Server Categories

  1. Official Reference Implementations:

    • Showcase MCP features and SDK usage
    • Maintained by Anthropic
    • Designed for reliability and clarity
    • Demonstrate protocol conformance

  2. Official Integrations:

    • Maintained by companies for their platforms
    • Production-ready implementations
    • Connect to specific services and APIs
    • Often include authentication workflows

  3. Community Servers:

    • Developed by community members
    • Cover diverse use cases and domains
    • Varying levels of maintenance and support
    • Unofficial and used at user's own risk

Implementation Steps

  1. Choose SDK:

    • TypeScript SDK for JavaScript/TypeScript development
    • Python SDK for Python development (often using fast-mcp)
    • Community implementations in other languages

  2. Define Server Logic:

    • Create tools that perform actions or query capabilities
    • Specify resources (documents or structured data)
    • Implement authentication if required

  3. Configure Transport:

    • Server-Sent Events (SSE) for web-based clients
    • Standard IO for local process communication
    • Custom transport layers for specific environments

  4. Handle Lifecycle:

    • Respond to initialization and capability discovery requests
    • Process tool calls and return results
    • Manage resources and state as needed

Server Architecture

Implementation Example

from model_context_protocol.server import Server
from model_context_protocol.fast_mcp import FastMCP

# Create server instance
server = FastMCP()

# Define and register tools
@server.tool("example_tool")
def example_tool(query: str) -> str:
    # Tool implementation logic
    return result
    
# Define and register resources
server.add_resource("example_resource", "path/to/resource.txt")

# Run the server with standard I/O
server.run(transport="stdio")

Express Servcer Implementation (Web Transport)

// Import necessary modules
import express from 'express';
import { MCPServer } from 'model-context-protocol';

// Create an Express server
const app = express();
const port = 881;

// Create MCP server instance
const server = new MCPServer();

// Define tools
server.addTool('getInventory', {
  description: 'Get the product inventory',
  parameters: {}, // Define parameters with Zod if needed
  execute: async () => {
    // Implementation logic to fetch inventory
    return JSON.stringify(inventory);
  }
});

// Set up SSE endpoint
app.get('/sse', (req, res) => {
  // SSE setup code
  // Establish the stateful connection between MCP client and server
});

// Set up messages endpoint
app.post('/sse/messages', (req, res) => {
  // Handle incoming messages from MCP clients
  // Process tool calls and return results
});

// Start the server
app.listen(port, () => {
  console.log(`MCP Server running on port ${port}`);
});

Host Application Configuration

{
  "mcpServers": {
    "example": {
      "command": "python",
      "args": ["-m", "example_server"],
      "env": {
        "API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

Security Considerations

Testing and Deployment

Key Reference Servers

Connections

References

  1. Model Context Protocol Implementation Guide: modelcontextprotocol.io/introduction
  2. TypeScript SDK: github.com/modelcontextprotocol/typescript-sdk
  3. Python SDK: github.com/modelcontextprotocol/python-sdk
  4. MCP Servers Repository: github.com/modelcontextprotocol/servers
  5. MCP Specification: modelcontextprotocol.io/specification

#MCP #MCPServer #ToolIntegration #AITools #ServerImplementation #JSON-RPC #LLMIntegration

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