# How to integrate Neverbounce MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Neverbounce MCP with Vercel AI SDK v6", "toolkit": "Neverbounce", "toolkit_slug": "neverbounce", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/neverbounce/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/neverbounce/framework/ai-sdk.md", "updated_at": "2026-05-12T10:20:05.703Z" } ``` ## Introduction This guide walks you through connecting Neverbounce to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Neverbounce agent that can verify a list of emails for bounces, download csv results from last bulk job, check your current neverbounce credit balance through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Neverbounce account through Composio's Neverbounce MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Neverbounce with - [OpenAI Agents SDK](https://composio.dev/toolkits/neverbounce/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/neverbounce/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/neverbounce/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/neverbounce/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/neverbounce/framework/codex) - [OpenClaw](https://composio.dev/toolkits/neverbounce/framework/openclaw) - [Hermes](https://composio.dev/toolkits/neverbounce/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/neverbounce/framework/cli) - [Google ADK](https://composio.dev/toolkits/neverbounce/framework/google-adk) - [LangChain](https://composio.dev/toolkits/neverbounce/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/neverbounce/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/neverbounce/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/neverbounce/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Neverbounce integration - Using Composio's Tool Router to dynamically load and access Neverbounce 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 Neverbounce MCP server, and what's possible with it? The Neverbounce MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Neverbounce account. It provides structured and secure access to your email verification tools, so your agent can perform actions like bulk verifying lists, checking job statuses, downloading results, and managing your account seamlessly. - Instant email verification and validation: Quickly verify email addresses for validity to reduce bounce rates and improve deliverability right from your agent. - Bulk email job management: Create, start, and track bulk verification jobs for entire email lists, letting your agent handle large-scale email hygiene automatically. - Automated job result retrieval: Download or fetch completed job results as CSVs or paginated data, making it easy to integrate verified emails into your workflows. - Account usage and credit tracking: Let your agent monitor account stats, credits, and usage so you always know your verification capacity and performance. - Secure job and data deletion: Direct your agent to permanently delete outdated or unnecessary jobs, ensuring your data remains clean and compliant. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `NEVERBOUNCE_ACCOUNT_INFO` | Get Account Info | Tool to get account information including credits, job counts, and usage statistics. Use when retrieving NeverBounce account summary after authentication. | | `NEVERBOUNCE_CONFIRM_POE` | Confirm Proof of Email | Tool to confirm proof of email ownership (POE) from the JavaScript widget. Use when verifying server-side that a user confirmed their email through the widget. | | `NEVERBOUNCE_JOBS_CREATE` | Create NeverBounce Bulk Verification Job | Tool to create a new bulk verification job with parsing, sampling, and callback options. Use for asynchronous list verification with advanced control. | | `NEVERBOUNCE_JOBS_DELETE` | Delete NeverBounce Job | Tool to permanently delete a job and its results. Use when you need to irreversibly remove a bulk verification job. This delete is irreversible. | | `NEVERBOUNCE_JOBS_DOWNLOAD_GET` | Download Job Results (GET) | Tool to download job results as a CSV file via GET. Use after job completion to retrieve segmented or enriched CSV output. | | `NEVERBOUNCE_JOBS_RESULTS` | Retrieve Job Results | Tool to retrieve paginated results for a completed job, including original data and verification outcomes. Use after confirming job completion; avoid aggressive polling as repeated calls before completion risk rate limit errors. | | `NEVERBOUNCE_JOBS_START` | Start NeverBounce Job | Tool to start a parsed job when auto_start is disabled. Use when you need to manually initiate a job that was created with auto_start=false. | | `NEVERBOUNCE_JOBS_STATUS` | Get bulk job status | Tool to get the status and progress of a bulk verification job. Use when | | `NEVERBOUNCE_PARSE_JOB` | Parse NeverBounce Job | Tool to parse a job created with auto_parse disabled. Use when you need to manually parse a job. Cannot reparse once parsed. | | `NEVERBOUNCE_SEARCH_JOBS` | Search bulk verification jobs | Tool to search and list bulk verification jobs in your account with pagination and filtering. Use when retrieving jobs by id, filename, or status, or when listing all jobs with pagination. | | `NEVERBOUNCE_SINGLE_CHECK` | NeverBounce Single Check | Tool to verify a single email address and gather additional information. Use when you need real-time validation at the point of entry. | | `NEVERBOUNCE_WIDGET_SEND_EVENT` | JS Widget Send Event | Tool to send widget form events via the JS widget API. Use when reporting form.load or form.completion events after user interactions with your form. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Neverbounce MCP server is an implementation of the Model Context Protocol that connects your AI agent to Neverbounce. It provides structured and secure access so your agent can perform Neverbounce 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 Neverbounce 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 Neverbounce-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: ["neverbounce"], }); 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 Neverbounce 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 neverbounce, 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 Neverbounce 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: ["neverbounce"], }); 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 neverbounce, 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 Neverbounce 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 Neverbounce MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/neverbounce/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/neverbounce/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/neverbounce/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/neverbounce/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/neverbounce/framework/codex) - [OpenClaw](https://composio.dev/toolkits/neverbounce/framework/openclaw) - [Hermes](https://composio.dev/toolkits/neverbounce/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/neverbounce/framework/cli) - [Google ADK](https://composio.dev/toolkits/neverbounce/framework/google-adk) - [LangChain](https://composio.dev/toolkits/neverbounce/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/neverbounce/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/neverbounce/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/neverbounce/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 Neverbounce MCP? With a standalone Neverbounce MCP server, the agents and LLMs can only access a fixed set of Neverbounce tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Neverbounce 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 Neverbounce tools. ### Can I manage the permissions and scopes for Neverbounce while using Tool Router? Yes, absolutely. You can configure which Neverbounce 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 Neverbounce data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)