Building AI Agents with Model Context Protocol

# Building AI Agents with Model Context Protocol The Model Context Protocol (MCP) is revolutionizing how AI agents interact with data sources and tools. Learn how to build powerful, context-aware AI agents. ## What is MCP? MCP provides a standardized interface for AI agents to: - Access external data sources - Execute tools and functions - Maintain context across interactions - Share knowledge between different AI systems ## Creating Your First MCP Server ```typescript import { MCPServer } from '@ainative/mcp'; const server = new MCPServer({ name: 'my-mcp-server', version: '1.0.0' }); // Define a tool server.tool({ name: 'search_database', description: 'Search the vector database', parameters: { query: { type: 'string', required: true }, limit: { type: 'number', default: 10 } }, handler: async ({ query, limit }) => { // Your search logic here return results; } }); server.start(); ``` ## Popular MCP Servers - **ZeroDB MCP**: Vector database integration - **Design System MCP**: AI-powered design tools - **shadcn/ui MCP**: UI component generation - **GitHub MCP**: Repository and code analysis ## Best Practices 1. **Clear Tool Descriptions**: Help the AI understand capabilities 2. **Proper Error Handling**: Graceful degradation 3. **Rate Limiting**: Protect your resources 4. **Security**: Validate all inputs Build smarter agents with MCP!

Building AI Agents with Model Context Protocol

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