Model Context Protocol

// MCP Configuration
const mcpConfig = {
  protocol: {
    version: "2.0",
    capabilities: ["tools", "resources", "prompts"]
  },
  tools: [
    {
      name: "file_reader",
      description: "Read and analyze code files",
      schema: {
        type: "object",
        properties: {
          path: { type: "string" },
          encoding: { type: "string", default: "utf-8" }
        }
      }
    }
  ],
  resources: [
    {
      uri: "file://src/**/*.ts",
      name: "TypeScript Source Files",
      mimeType: "text/typescript"
    }
  ]
};

// Initialize MCP Client
const client = new MCPClient(mcpConfig);
await client.connect("stdio");

// Context-aware code generation
const contextResult = await mcp.generateWithContext({
  prompt: "Add error handling to this function",
  context: {
    currentFile: "src/api/users.ts",
    codebase: await mcp.scanCodebase(),
    dependencies: ["express", "joi", "prisma"],
    testFramework: "jest"
  },
  model: "claude-3-opus"
});

console.log(contextResult.enhancedCode);
console.log(contextResult.explanation);

// Real-time streaming with MCP
const stream = mcp.createStream({
  model: "gpt-4",
  temperature: 0.1
});

stream.on('token', (token) => {
  process.stdout.write(token);
});

stream.on('tool_call', (toolCall) => {
  console.log(`Using tool: ${toolCall.name}`);
});

await stream.send({
  prompt: "Refactor this React component to use TypeScript",
  files: ["components/UserProfile.jsx"]
});