# How to integrate Zoominfo MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Zoominfo MCP with Vercel AI SDK v6", "toolkit": "Zoominfo", "toolkit_slug": "zoominfo", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/zoominfo/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/zoominfo/framework/ai-sdk.md", "updated_at": "2026-05-06T08:35:12.735Z" } ``` ## Introduction This guide walks you through connecting Zoominfo to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Zoominfo agent that can find companies in new york with over 500 employees, enrich this contact with latest job title, list recent news about target accounts through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Zoominfo account through Composio's Zoominfo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Zoominfo with - [OpenAI Agents SDK](https://composio.dev/toolkits/zoominfo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zoominfo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zoominfo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zoominfo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zoominfo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zoominfo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zoominfo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zoominfo/framework/cli) - [Google ADK](https://composio.dev/toolkits/zoominfo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zoominfo/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/zoominfo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zoominfo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zoominfo/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Zoominfo integration - Using Composio's Tool Router to dynamically load and access Zoominfo 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 Zoominfo MCP server, and what's possible with it? The Zoominfo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zoominfo account. It provides structured and secure access to rich B2B sales intelligence, so your agent can search companies, enrich contact and company data, analyze intent signals, and surface actionable go-to-market insights for you. - Company and contact data enrichment: Instantly have your agent pull detailed profiles, firmographics, and contact information for any business or person of interest. - Smart company and contact search: Let your agent find the right leads by searching Zoominfo's vast database using criteria like location, industry, and role. - Intent signal analysis: Enable your agent to analyze buying intent signals and help prioritize outreach based on real-time market activity. - Technology and news enrichment: Ask your agent to uncover what technologies a company uses or find the latest news and scoops about prospects and clients. - Location-based prospecting: Have your agent filter and enrich location details to support precise territory planning and targeted campaigns. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ZOOMINFO_ENRICH_COMPANY` | Company Enrich | Company enrich | | `ZOOMINFO_ENRICH_CONTACT` | Contact Enrich | Contact enrich | | `ZOOMINFO_ENRICH_INTENT` | Intent Enrich | Intent enrich | | `ZOOMINFO_ENRICH_LOCATION` | Location Enrich | Location enrich | | `ZOOMINFO_ENRICH_NEWS` | News Enrich | News enrich | | `ZOOMINFO_ENRICH_SCOOP` | Scoop Enrich | Scoop enrich | | `ZOOMINFO_ENRICH_TECHNOLOGY` | Technology Enrich | Technology enrich | | `ZOOMINFO_SEARCH_COMPANY` | Company Search | Returns a list of companies from zoominfo's data which meet the specified search criteria. | | `ZOOMINFO_SEARCH_COMPANY_INPUT` | Company Search Inputs | Returns a list of fields you can use as input for the company search action. | | `ZOOMINFO_SEARCH_CONTACT` | Contact Search | Returns a list of contacts from zoominfo's data that meet the specified search criteria. | | `ZOOMINFO_SEARCH_CONTACT_INPUT` | Contact Search Inputs | Returns a list of fields you can use as input for the contact search action. | | `ZOOMINFO_SEARCH_INTENT` | Intent Search | Use this endpoint to search for companies and recommended contacts based on intent data. use input values to return the desired output fields in the response. for charging purposes, each intent signal returned is counted as a record. | | `ZOOMINFO_SEARCH_INTENT_INPUT` | Intent Search Inputs | Returns a list of fields you can use as input for the intent action. | | `ZOOMINFO_SEARCH_NEWS` | News Search | Returns a list of news articles from zoominfo's data which meet the specified search criteria. all inputs are optional, but you must use at least one input parameter to generate a successful response. | | `ZOOMINFO_SEARCH_NEWS_INPUT` | News Search Inputs | Returns a list of fields you can use as input for the news search endpoint. | | `ZOOMINFO_SEARCH_SCOOP` | Scoop Search | Returns a list of scoops from zoominfo's data which meet the specified search criteria. | | `ZOOMINFO_SEARCH_SCOOP_INPUT` | Scoop Search Inputs | Returns a list of fields you can use as input for the scoop search action. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Zoominfo MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zoominfo. It provides structured and secure access so your agent can perform Zoominfo 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 Zoominfo 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 Zoominfo-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: ["zoominfo"], }); 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 Zoominfo 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 zoominfo, 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 Zoominfo 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("\n๐Ÿ‘‹ 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: ["zoominfo"], }); 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 zoominfo, 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("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Zoominfo 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 Zoominfo MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/zoominfo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zoominfo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zoominfo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zoominfo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zoominfo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zoominfo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zoominfo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zoominfo/framework/cli) - [Google ADK](https://composio.dev/toolkits/zoominfo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zoominfo/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/zoominfo/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zoominfo/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zoominfo/framework/crew-ai) ## Related Toolkits - [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place. - [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up. - [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships. - [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place. - [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently. - [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing. - [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. - [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities. - [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place. - [Bettercontact](https://composio.dev/toolkits/bettercontact) - Bettercontact is a smart contact enrichment tool for finding emails and phone numbers. It helps boost lead generation with automated, waterfall search across multiple sources. - [Blackbaud](https://composio.dev/toolkits/blackbaud) - Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations. - [Brilliant directories](https://composio.dev/toolkits/brilliant_directories) - Brilliant Directories is an all-in-one platform for building and managing online membership communities and business directories. It streamlines listings, member management, and engagement tools into a single, easy interface. - [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently. - [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time. - [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools. - [Dropcontact](https://composio.dev/toolkits/dropcontact) - Dropcontact is a B2B email finder and data enrichment service for professionals. It delivers verified email addresses and enriches contact info with up-to-date data. - [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place. - [Espocrm](https://composio.dev/toolkits/espocrm) - EspoCRM is an open-source web application for managing customer relationships. It helps businesses organize contacts, track leads, and streamline their sales process. - [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Zoominfo MCP? With a standalone Zoominfo MCP server, the agents and LLMs can only access a fixed set of Zoominfo tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zoominfo 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 Zoominfo tools. ### Can I manage the permissions and scopes for Zoominfo while using Tool Router? Yes, absolutely. You can configure which Zoominfo 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 Zoominfo data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)