# How to integrate Zerobounce MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Zerobounce MCP with Vercel AI SDK v6", "toolkit": "Zerobounce", "toolkit_slug": "zerobounce", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/zerobounce/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/zerobounce/framework/ai-sdk.md", "updated_at": "2026-05-06T08:34:42.363Z" } ``` ## Introduction This guide walks you through connecting Zerobounce to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Zerobounce agent that can validate a list of 100 new signups, score this email for lead quality, check deliverability of mark@gmail.com through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Zerobounce account through Composio's Zerobounce MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Zerobounce with - [OpenAI Agents SDK](https://composio.dev/toolkits/zerobounce/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zerobounce/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zerobounce/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zerobounce/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zerobounce/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zerobounce/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zerobounce/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zerobounce/framework/cli) - [Google ADK](https://composio.dev/toolkits/zerobounce/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zerobounce/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/zerobounce/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zerobounce/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zerobounce/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Zerobounce integration - Using Composio's Tool Router to dynamically load and access Zerobounce 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 Zerobounce MCP server, and what's possible with it? The Zerobounce MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zerobounce account. It provides structured and secure access to your email validation and deliverability tools, so your agent can perform actions like validating emails, scoring leads, managing bulk jobs, and analyzing engagement—all automatically. - Real-time email validation: Instantly check if email addresses are valid, risky, or undeliverable before sending campaigns or updating your lists. - Bulk validation and processing: Upload files and process hundreds of emails or domains at once, with tools for tracking job status and retrieving results. - AI-powered lead scoring: Score individual email addresses using Zerobounce AI to assess lead quality and prioritize outreach. - Domain and pattern analysis: Identify common email address formats for any domain or run bulk domain searches to optimize your contact strategies. - Allowlist and blocklist management: Easily update your allow and block lists to fine-tune which addresses pass or fail validation, keeping your lists clean and secure. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ZEROBOUNCE_ACTIVITY_DATA` | Get Activity Data | Tool to get activity data (opens, clicks, etc.) for a given email. use after confirming the email address to gauge engagement recency. | | `ZEROBOUNCE_AI_SCORING_SINGLE` | AI Scoring Single Email | Tool to score a single email address using zerobounce ai. use when you need real-time email lead quality feedback before outreach. example prompt: "score the email mark@gmail.com." | | `ZEROBOUNCE_ALLOW_BLOCK_LIST` | Allow or Block List | Tool to manage allowlist and blocklist for email validation. use when you need to programmatically add or modify custom filters before validating emails. | | `ZEROBOUNCE_BATCH_VALIDATE_EMAILS` | Batch Validate Emails | Tool to validate a batch of email addresses in real time. use when you need to validate up to 200 emails at once with optional activity data. | | `ZEROBOUNCE_DELETE_FILE` | Delete file | Tool to delete a file that was submitted for bulk validation. use when file status is 'complete'. | | `ZEROBOUNCE_DOMAIN_SEARCH_FILE_STATUS` | Domain Search File Status | Tool to get the processing status of a file submitted for bulk domain search. use after submitting the file to poll status. | | `ZEROBOUNCE_DOMAIN_SEARCH_GET_FILE` | Domain Search Get File | Tool to download the results file for a completed bulk domain search job. use when you have the file id and the job is complete. | | `ZEROBOUNCE_DOMAIN_SEARCH_SEND_FILE` | Domain Search Send File | Tool to upload a file for bulk domain search. use when you have many domains in a csv/txt and need to lookup their details in bulk. | | `ZEROBOUNCE_DOMAIN_SEARCH_SINGLE` | Domain Search Single | Tool to identify common email address formats for a given domain. use when you need to guess email patterns for a company based on its domain. | | `ZEROBOUNCE_EMAIL_FINDER_DELETE_FILE` | Delete Email Finder File | Tool to delete a file that was submitted for bulk email finding. use when the file processing status is 'complete' and you need to remove it. | | `ZEROBOUNCE_EMAIL_FINDER_FILE_STATUS` | Email Finder File Status | Tool to get the processing status of a file submitted for bulk email finding. use when you need to poll the progress of a bulk email-finder file upload. | | `ZEROBOUNCE_EMAIL_FINDER_SEND_FILE` | Email Finder Send File | Tool to upload a file for bulk email finding. use when you have lists of names and domains to find emails in bulk via csv/txt upload. | | `ZEROBOUNCE_EMAIL_FINDER_SINGLE` | Email Finder Single | Tool to find an email address for a given person and domain. use when you need to locate a professional email from a person's name and company domain. use after confirming domain or company info. | | `ZEROBOUNCE_GET_API_USAGE` | Get API Usage | Tool to retrieve api usage statistics for a given period. use when you need usage metrics between two dates. | | `ZEROBOUNCE_GET_CREDIT_BALANCE` | Get Credit Balance | Tool to retrieve your current zerobounce email validation credit balance. use when you need to monitor remaining credits to avoid service interruptions. | | `ZEROBOUNCE_LIST_EVALUATOR` | List Evaluator | Tool to evaluate the quality of an email list. use when you have a list of emails and need a quick health check before full validation. | | `ZEROBOUNCE_SEND_FILE` | Send File | Tool to upload a file for bulk email validation. use when you need to validate large lists of emails via csv or txt file. | | `ZEROBOUNCE_VALIDATE_EMAIL` | Validate Email | Tool to validate a single email address in real time. use when you need to confirm deliverability and domain details before sending emails. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Zerobounce MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zerobounce. It provides structured and secure access so your agent can perform Zerobounce 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 Zerobounce 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 Zerobounce-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: ["zerobounce"], }); 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 Zerobounce 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 zerobounce, 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 Zerobounce 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: ["zerobounce"], }); 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 zerobounce, 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 Zerobounce 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 Zerobounce MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/zerobounce/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zerobounce/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zerobounce/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zerobounce/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zerobounce/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zerobounce/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zerobounce/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zerobounce/framework/cli) - [Google ADK](https://composio.dev/toolkits/zerobounce/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zerobounce/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/zerobounce/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zerobounce/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zerobounce/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Zerobounce MCP? With a standalone Zerobounce MCP server, the agents and LLMs can only access a fixed set of Zerobounce tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zerobounce 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 Zerobounce tools. ### Can I manage the permissions and scopes for Zerobounce while using Tool Router? Yes, absolutely. You can configure which Zerobounce 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 Zerobounce data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)