# How to integrate La Growth Machine MCP with Vercel AI SDK v6 ```json { "title": "How to integrate La Growth Machine MCP with Vercel AI SDK v6", "toolkit": "La Growth Machine", "toolkit_slug": "lagrowthmachine", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/lagrowthmachine/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/lagrowthmachine/framework/ai-sdk.md", "updated_at": "2026-03-29T06:39:56.150Z" } ``` ## Introduction This guide walks you through connecting La Growth Machine to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working La Growth Machine agent that can launch a multi-channel campaign for new leads, get outreach stats for this week's campaigns, add a contact to your sales pipeline through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a La Growth Machine account through Composio's La Growth Machine MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate La Growth Machine with - [OpenAI Agents SDK](https://composio.dev/toolkits/lagrowthmachine/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/lagrowthmachine/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/lagrowthmachine/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/lagrowthmachine/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/lagrowthmachine/framework/codex) - [OpenClaw](https://composio.dev/toolkits/lagrowthmachine/framework/openclaw) - [Hermes](https://composio.dev/toolkits/lagrowthmachine/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/lagrowthmachine/framework/cli) - [Google ADK](https://composio.dev/toolkits/lagrowthmachine/framework/google-adk) - [LangChain](https://composio.dev/toolkits/lagrowthmachine/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/lagrowthmachine/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/lagrowthmachine/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/lagrowthmachine/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with La Growth Machine integration - Using Composio's Tool Router to dynamically load and access La Growth Machine tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the La Growth Machine MCP server, and what's possible with it? The La Growth Machine MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your La Growth Machine account. It provides structured and secure access so your agent can perform La Growth Machine operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LAGROWTHMACHINE_ADD_RB2B_VISITOR_TO_AUDIENCE` | Add RB2B Visitor to Audience | Tool to add RB2B website visitor to a LaGrowthMachine audience via native webhook. Use when you need to push identified website visitors from RB2B into a specific audience for outreach campaigns. | | `LAGROWTHMACHINE_CREATE_AUDIENCE_FROM_LINKEDIN_URL` | Create Audience from LinkedIn URL | Tool to import leads into La Growth Machine audiences from LinkedIn URLs. Accepts LinkedIn Regular search URLs, Sales Navigator search URLs, or LinkedIn post URLs. Requires specifying the identity to impersonate and the audience name to populate. | | `LAGROWTHMACHINE_CREATE_INBOX_WEBHOOK` | Create Inbox Webhook | Tool to create an inbox webhook for real-time notifications. Use when you need to receive notifications about LinkedIn and Email messages sent or received by leads in La Growth Machine campaigns. | | `LAGROWTHMACHINE_CREATE_OR_UPDATE_LEAD` | Create or Update Lead | Tool to create or update a lead in LaGrowthMachine. Requires audience plus at least one identifier: proEmail, persoEmail, linkedinUrl, twitter, or firstname+lastname with companyUrl/companyName. Use leadId to update an existing lead. | | `LAGROWTHMACHINE_DELETE_INBOX_WEBHOOK` | Delete Inbox Webhook | Tool to delete an existing inbox webhook by its ID. Use when you need to stop receiving inbox events at the webhook URL. | | `LAGROWTHMACHINE_GET_CAMPAIGNS` | Get Campaigns | Tool to retrieve all campaigns from LaGrowthMachine with pagination support. Use when you need to list campaigns, with optional skip and limit parameters for pagination (max 25 per page). | | `LAGROWTHMACHINE_LIST_AUDIENCES` | List Audiences | Tool to list all audiences in your LaGrowthMachine account. Use when you need to retrieve audience details including ID, name, description, size, type, and source URL. | | `LAGROWTHMACHINE_LIST_IDENTITIES` | List Identities | Tool to list all connected identities in your LaGrowthMachine account. Use when you need to retrieve identity IDs for sending LinkedIn or Email messages through other APIs. | | `LAGROWTHMACHINE_LIST_INBOX_WEBHOOKS` | List Inbox Webhooks | Tool to list all inbox webhooks currently configured in your workspace. Use when you need to retrieve webhook IDs, names, and target URLs for webhook management or audit purposes. | | `LAGROWTHMACHINE_LIST_MEMBERS` | List Members | Tool to list all members (users) associated with your workspace. Use when you need to retrieve member information, especially memberId which is required for action-based endpoints like sending LinkedIn or Email messages. | | `LAGROWTHMACHINE_REGISTER_VECTOR_VISITOR_WEBHOOK` | Register Vector Visitor Webhook | Tool to register Vector website visitors to a La Growth Machine audience. Use when receiving visitor events from Vector integration to automatically add identified contacts to the specified audience. | | `LAGROWTHMACHINE_REMOVE_LEAD_FROM_AUDIENCES` | Remove Lead From Audiences | Tool to remove a lead from one or more specified audiences in La Growth Machine. Use when you need to unsubscribe or remove a lead from audience lists. | | `LAGROWTHMACHINE_SEARCH_LEAD` | Search Lead | Tool to search for a lead using various criteria. Use when you need to find a lead by email, LinkedIn URL, lead ID, or name combination. At least one of these must be provided: email, linkedinUrl, leadId, or firstname+lastname+(companyName or companyUrl). | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The La Growth Machine MCP server is an implementation of the Model Context Protocol that connects your AI agent to La Growth Machine. It provides structured and secure access so your agent can perform La Growth Machine operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to La Growth Machine tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all La Growth Machine-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["lagrowthmachine"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available La Growth Machine tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to lagrowthmachine, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use La Growth Machine tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["lagrowthmachine"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to lagrowthmachine, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a La Growth Machine agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build La Growth Machine MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/lagrowthmachine/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/lagrowthmachine/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/lagrowthmachine/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/lagrowthmachine/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/lagrowthmachine/framework/codex) - [OpenClaw](https://composio.dev/toolkits/lagrowthmachine/framework/openclaw) - [Hermes](https://composio.dev/toolkits/lagrowthmachine/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/lagrowthmachine/framework/cli) - [Google ADK](https://composio.dev/toolkits/lagrowthmachine/framework/google-adk) - [LangChain](https://composio.dev/toolkits/lagrowthmachine/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/lagrowthmachine/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/lagrowthmachine/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/lagrowthmachine/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations. - [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place. - [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Basin](https://composio.dev/toolkits/basin) - Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code. - [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives. - [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates. - [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and La Growth Machine MCP? With a standalone La Growth Machine MCP server, the agents and LLMs can only access a fixed set of La Growth Machine tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from La Growth Machine and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right La Growth Machine tools. ### Can I manage the permissions and scopes for La Growth Machine while using Tool Router? Yes, absolutely. You can configure which La Growth Machine scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your La Growth Machine data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)