Pipedream MCP with Gemini

npm install @google/generativeai @modelcontextprotocol/sdk @pipedream/sdk

import { GoogleGenerativeAI } from '@google/generativeai';
import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js';
import { PipedreamClient } from '@pipedream/sdk';

// Environment variables
const GOOGLE_API_KEY = process.env.GOOGLE_API_KEY!;
const PIPEDREAM_CLIENT_ID = process.env.PIPEDREAM_CLIENT_ID!;
const PIPEDREAM_CLIENT_SECRET = process.env.PIPEDREAM_CLIENT_SECRET!;
const PIPEDREAM_PROJECT_ID = process.env.PIPEDREAM_PROJECT_ID!;
const PIPEDREAM_ENVIRONMENT = process.env.PIPEDREAM_ENVIRONMENT as 'development' | 'production';

async function runGeminiWithMCP() {
  // Initialize Pipedream SDK client
  const pdClient = new PipedreamClient({
    projectEnvironment: PIPEDREAM_ENVIRONMENT,
    clientId: PIPEDREAM_CLIENT_ID,
    clientSecret: PIPEDREAM_CLIENT_SECRET,
    projectId: PIPEDREAM_PROJECT_ID
  });

  // Get access token for MCP authentication
  const accessToken = await pdClient.rawAccessToken;
  const externalUserId = 'user-123'; // Your user's unique ID
  const appSlug = 'gmail,google_calendar'; // Apps to use

  // Create MCP transport
  const transport = new StreamableHTTPClientTransport(
    new URL('https://remote.mcp.pipedream.net/v3'),
    {
      requestInit: {
        headers: {
          'Authorization': `Bearer ${accessToken}`,
          'x-pd-project-id': PIPEDREAM_PROJECT_ID,
          'x-pd-environment': PIPEDREAM_ENVIRONMENT,
          'x-pd-external-user-id': externalUserId,
          'x-pd-app-slug': appSlug,
        }
      }
    }
  );

  // Initialize MCP client
  const mcpClient = new Client({
    name: 'gemini-pipedream-client',
    version: '1.0.0',
  });

  await mcpClient.connect(transport);

  // Initialize Gemini client
  const genAI = new GoogleGenerativeAI(GOOGLE_API_KEY);
  
  try {
    // Get available tools from MCP
    const toolsResponse = await mcpClient.listTools();
    const mcpTools = toolsResponse.tools || [];

    // Convert MCP tools to Gemini function calling format
    const geminiTools = mcpTools.map((tool: any) => ({
      function_declarations: [{
        name: tool.name,
        description: tool.description,
        parameters: tool.inputSchema,
      }]
    }));

    // Create model with tools
    const model = genAI.getGenerativeModel({
      model: 'gemini-pro',
      tools: geminiTools,
      systemInstruction: `You are a helpful AI assistant with access to powerful tools.
      
The current date is ${new Date().toISOString().split('T')[0]}.

Use the available tools to help users accomplish their tasks effectively.
If you encounter any errors, explain what happened and suggest alternatives.`
    });

    // Start chat
    const chat = model.startChat({
      history: [],
    });

    const userMessage = "Check my recent emails and summarize the important ones";
    console.log(`User: ${userMessage}`);

    // Send message and handle tool calls
    const result = await chat.sendMessage(userMessage);
    const response = await result.response;

    // Handle function calls if present
    if (response.functionCalls?.length > 0) {
      console.log('Executing tools...');
      
      const functionResults = [];
      
      for (const functionCall of response.functionCalls) {
        try {
          const result = await mcpClient.callTool({
            name: functionCall.name,
            arguments: functionCall.args,
          });
          
          functionResults.push({
            name: functionCall.name,
            response: result,
          });
          
          console.log(`✅ ${functionCall.name}: Success`);
        } catch (error) {
          console.error(`❌ ${functionCall.name}: ${error}`);
          functionResults.push({
            name: functionCall.name,
            response: { error: String(error) },
          });
        }
      }

      // Send function results back to Gemini
      const finalResult = await chat.sendMessage([{
        functionResponse: {
          name: functionResults[0].name,
          response: functionResults[0].response,
        }
      }]);

      console.log(`Gemini: ${finalResult.response.text()}`);
    } else {
      console.log(`Gemini: ${response.text()}`);
    }

  } finally {
    // Clean up MCP client
    await mcpClient.close();
  }
}

// Run the example
runGeminiWithMCP().catch(console.error);