Model Context Protocol (MCP) 2026: Building AI Tool Integrations

// Basic MCP Server
import { Server } from '@modelcontextprotocol/sdk/server/index.js';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';

const server = new Server(
  {
    name: 'my-mcp-server',
    version: '1.0.0',
  },
  {
    capabilities: {
      tools: {},
      resources: {},
    },
  }
);

// Define a tool
server.setRequestHandler('tools/list', async () => ({
  tools: [
    {
      name: 'search_database',
      description: 'Search the database for records',
      inputSchema: {
        type: 'object',
        properties: {
          query: { type: 'string', description: 'Search query' },
          limit: { type: 'number', description: 'Max results' },
        },
        required: ['query'],
      },
    },
  ],
}));

// Handle tool calls
server.setRequestHandler('tools/call', async (request) => {
  if (request.params.name === 'search_database') {
    const { query, limit = 10 } = request.params.arguments;
    const results = await db.search(query, limit);
    return { content: [{ type: 'text', text: JSON.stringify(results) }] };
  }
  throw new Error('Unknown tool');
});

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

// MCP Resources (data the LLM can read)
server.setRequestHandler('resources/list', async () => ({
  resources: [
    {
      uri: 'db://users/schema',
      name: 'Database Schema',
      description: 'Current database schema',
      mimeType: 'application/json',
    },
  ],
}));

server.setRequestHandler('resources/read', async (request) => {
  if (request.params.uri === 'db://users/schema') {
    const schema = await db.getSchema();
    return {
      contents: [{
        uri: request.params.uri,
        mimeType: 'application/json',
        text: JSON.stringify(schema),
      }],
    };
  }
  throw new Error('Resource not found');
});