# How to integrate Findymail MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Findymail MCP with Vercel AI SDK v6", "toolkit": "Findymail", "toolkit_slug": "findymail", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/findymail/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/findymail/framework/ai-sdk.md", "updated_at": "2026-05-12T10:11:28.700Z" } ``` ## Introduction This guide walks you through connecting Findymail to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Findymail agent that can find verified email for john at acme.com, create a new contact list for leads, verify deliverability of this email address through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Findymail account through Composio's Findymail MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Findymail with - [OpenAI Agents SDK](https://composio.dev/toolkits/findymail/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/findymail/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/findymail/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/findymail/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/findymail/framework/codex) - [OpenClaw](https://composio.dev/toolkits/findymail/framework/openclaw) - [Hermes](https://composio.dev/toolkits/findymail/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/findymail/framework/cli) - [Google ADK](https://composio.dev/toolkits/findymail/framework/google-adk) - [LangChain](https://composio.dev/toolkits/findymail/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/findymail/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/findymail/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/findymail/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Findymail integration - Using Composio's Tool Router to dynamically load and access Findymail 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 Findymail MCP server, and what's possible with it? The Findymail MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Findymail account. It provides structured and secure access to verified B2B contact data, so your agent can create and manage contact lists, find and verify emails, and streamline your outreach workflow automatically. - Automated contact list management: Let your agent create new contact lists, fetch all your lists, or delete lists as your prospecting needs change. - Precise contact discovery: Ask your agent to find and retrieve emails for prospects based on full name and company domain, making it easier to build targeted outreach campaigns. - Bulk contact retrieval: Direct your agent to list all contacts within a specific list, enabling quick access to leads for export or follow-up. - Email deliverability verification: Have your agent check if an email address is valid and safe to use before sending that crucial first message. - Seamless CRM enrichment: Use verified contact details to automatically enrich your CRM, helping you keep data accurate and actionable for your sales team. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `FINDYMAIL_ADD_EXCLUDED_DOMAIN` | Add Excluded Domain | Tool to add domains to an exclusion list in Findymail. Use when you need to prevent email searches or verification for specific domains. | | `FINDYMAIL_CREATE_EXCLUSION_LIST` | Create Exclusion List | Tool to create a new exclusion list for Intellimatch searches. Use when you need to filter out specific companies or contacts from search results. | | `FINDYMAIL_CREATE_LIST` | Create Contact List | Tool to create a new contact list. Use when you need to organize contacts into a named list before adding them. | | `FINDYMAIL_DELETE_EXCLUSION_LIST` | Delete Exclusion List | Tool to permanently delete an exclusion list by its ID. Use when you need to remove an exclusion list from Intellimatch. This action is irreversible. | | `FINDYMAIL_DELETE_LIST` | Delete Contact List | Permanently deletes a contact list by its ID. This action is irreversible and will also remove all contacts in the list. Returns 404 if the list does not exist. | | `FINDYMAIL_FIND_EMAIL_BY_NAME` | Find Email by Name | Tool to find someone's email using their full name and company domain. Use when you have a person's name and domain and need their email address. Supports asynchronous search via webhook_url. | | `FINDYMAIL_GET_CONTACT_LISTS` | Get Contact Lists | Tool to retrieve all contact lists. Use when you need an overview of your existing Findymail lists. | | `FINDYMAIL_GET_CREDITS` | Get Credits | Tool to check available API credits for your Findymail account. Use when you need to verify remaining credits before performing operations. | | `FINDYMAIL_GET_CREDITS_SUMMARY` | Get Credits Summary | Tool to retrieve credits usage summary report for the authenticated account. Use when you need to check credits consumption over time. | | `FINDYMAIL_GET_CREDITS_TEAM_SUMMARY` | Get Credits Team Summary | Tool to retrieve team credits usage summary report. Use when you need an overview of credit consumption across team members. | | `FINDYMAIL_GET_EXCLUSION_LIST` | Get Exclusion List | Tool to retrieve a specific exclusion list by ID. Use when you need details about a particular exclusion list. | | `FINDYMAIL_GET_INTELLIMATCH_DATA` | Get Intellimatch Data | Tool to retrieve data from an Intellimatch search. Use after initiating a search with POST /api/intellimatch/search and confirming completion with GET /api/intellimatch/status. | | `FINDYMAIL_GET_INTELLIMATCH_STATUS` | Get Intellimatch Status | Tool to check the status of an Intellimatch search job. Use when you need to verify if an Intellimatch search has completed after initiating it. | | `FINDYMAIL_LIST_CONTACTS` | List Contacts | Tool to retrieve contacts from a specified list (paginated). Use after selecting a list to fetch its contacts. | | `FINDYMAIL_LIST_EXCLUDED_DOMAINS` | List Excluded Domains | Tool to retrieve domains excluded from Intellimatch searches. Use when you need to view the current domain exclusion list. | | `FINDYMAIL_LIST_EXCLUSION_LISTS` | List Exclusion Lists | Tool to retrieve all exclusion lists for managing excluded websites from Intellimatch searches. Use when you need to view configured website exclusions. | | `FINDYMAIL_REMOVE_EXCLUDED_DOMAIN` | Remove Excluded Domain | Tool to remove domains from the exclusion list. Use when you need to stop excluding specific domains from email search results. | | `FINDYMAIL_SEARCH_INTELLIMATCH` | Search Intellimatch | Tool to find companies and contacts using natural language queries. Use when you need to build targeted lead lists automatically by describing your ideal customer profile in plain language. | | `FINDYMAIL_UPDATE_EXCLUSION_LIST` | Update Exclusion List | Tool to update an existing exclusion list. Use when you need to rename or modify an exclusion list's properties. | | `FINDYMAIL_UPDATE_LIST` | Update Contact List | Tool to update an existing contact list. Use when you need to rename a list or change its sharing settings. | | `FINDYMAIL_VERIFY_EMAIL` | Verify Email | Tool to verify the deliverability of an email address. Use when you need to confirm an email can receive messages before outreach. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Findymail MCP server is an implementation of the Model Context Protocol that connects your AI agent to Findymail. It provides structured and secure access so your agent can perform Findymail 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 Findymail 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 Findymail-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: ["findymail"], }); 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 Findymail 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 findymail, 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 Findymail 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: ["findymail"], }); 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 findymail, 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 Findymail 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 Findymail MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/findymail/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/findymail/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/findymail/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/findymail/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/findymail/framework/codex) - [OpenClaw](https://composio.dev/toolkits/findymail/framework/openclaw) - [Hermes](https://composio.dev/toolkits/findymail/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/findymail/framework/cli) - [Google ADK](https://composio.dev/toolkits/findymail/framework/google-adk) - [LangChain](https://composio.dev/toolkits/findymail/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/findymail/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/findymail/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/findymail/framework/crew-ai) ## Related Toolkits - [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. - [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. - [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. - [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations. - [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code. - [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding. - [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls. - [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources. - [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates. - [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly. - [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. - [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality. - [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster. - [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support. - [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach. - [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback. - [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Findymail MCP? With a standalone Findymail MCP server, the agents and LLMs can only access a fixed set of Findymail tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Findymail 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 Findymail tools. ### Can I manage the permissions and scopes for Findymail while using Tool Router? Yes, absolutely. You can configure which Findymail 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 Findymail data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)