# How to integrate Zerobounce MCP with LangChain ```json { "title": "How to integrate Zerobounce MCP with LangChain", "toolkit": "Zerobounce", "toolkit_slug": "zerobounce", "framework": "LangChain", "framework_slug": "langchain", "url": "https://composio.dev/toolkits/zerobounce/framework/langchain", "markdown_url": "https://composio.dev/toolkits/zerobounce/framework/langchain.md", "updated_at": "2026-05-06T08:34:42.363Z" } ``` ## Introduction This guide walks you through connecting Zerobounce to LangChain 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 LangChain 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) - [Vercel AI SDK](https://composio.dev/toolkits/zerobounce/framework/ai-sdk) - [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: - Get and set up your OpenAI and Composio API keys - Connect your Zerobounce project to Composio - Create a Tool Router MCP session for Zerobounce - Initialize an MCP client and retrieve Zerobounce tools - Build a LangChain agent that can interact with Zerobounce - Set up an interactive chat interface for testing ## What is LangChain? LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context. Key features include: - Agent Framework: Build agents that can use tools and make decisions - MCP Integration: Connect to external services through Model Context Protocol adapters - Memory Management: Maintain conversation history across interactions - Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers ## 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 No description provided. ### 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 dependencies No description provided. ```python pip install composio-langchain langchain-mcp-adapters langchain python-dotenv ``` ```typescript npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your requests to Composio's API - COMPOSIO_USER_ID identifies the user for session management - OPENAI_API_KEY enables access to OpenAI's language models ```bash COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_composio_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies No description provided. ```python from langchain_mcp_adapters.client import MultiServerMCPClient from langchain.agents import create_agent from dotenv import load_dotenv from composio import Composio import asyncio import os load_dotenv() ``` ```typescript import { Composio } from '@composio/core'; import { LangchainProvider } from '@composio/langchain'; import { MultiServerMCPClient } from "@langchain/mcp-adapters"; import { createAgent } from "langchain"; import * as readline from 'readline'; import 'dotenv/config'; dotenv.config(); ``` ### 5. Initialize Composio client What's happening: - We're loading the COMPOSIO_API_KEY from environment variables and validating it exists - Creating a Composio instance that will manage our connection to Zerobounce tools - Validating that COMPOSIO_USER_ID is also set before proceeding ```python async def main(): composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) if not os.getenv("COMPOSIO_API_KEY"): raise ValueError("COMPOSIO_API_KEY is not set") if not os.getenv("COMPOSIO_USER_ID"): raise ValueError("COMPOSIO_USER_ID is not set") ``` ```typescript const composioApiKey = process.env.COMPOSIO_API_KEY; const userId = process.env.COMPOSIO_USER_ID; if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set'); if (!userId) throw new Error('COMPOSIO_USER_ID is not set'); async function main() { const composio = new Composio({ apiKey: composioApiKey as string, provider: new LangchainProvider() }); ``` ### 6. Create a Tool Router session 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 session.mcp.url is the MCP server URL that your agent will use - This approach allows the agent to dynamically load and use Zerobounce tools as needed ```python # Create Tool Router session for Zerobounce session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['zerobounce'] ) url = session.mcp.url ``` ```typescript const session = await composio.create( userId as string, { toolkits: ['zerobounce'] } ); const url = session.mcp.url; ``` ### 7. Configure the agent with the MCP URL No description provided. ```python client = MultiServerMCPClient({ "zerobounce-agent": { "transport": "streamable_http", "url": session.mcp.url, "headers": { "x-api-key": os.getenv("COMPOSIO_API_KEY") } } }) tools = await client.get_tools() agent = create_agent("gpt-5", tools) ``` ```typescript const client = new MultiServerMCPClient({ "zerobounce-agent": { transport: "http", url: url, headers: { "x-api-key": process.env.COMPOSIO_API_KEY } } }); const tools = await client.getTools(); const agent = createAgent({ model: "gpt-5", tools }); ``` ### 8. Set up interactive chat interface No description provided. ```python conversation_history = [] print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Zerobounce related question or task to the agent.\n") while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue conversation_history.append({"role": "user", "content": user_input}) print("\nAgent is thinking...\n") response = await agent.ainvoke({"messages": conversation_history}) conversation_history = response['messages'] final_response = response['messages'][-1].content print(f"Agent: {final_response}\n") ``` ```typescript let conversationHistory: any[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log("Ask any Zerobounce related question or task to the agent.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: 'You: ' }); 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; } conversationHistory.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); const response = await agent.invoke({ messages: conversationHistory }); conversationHistory = response.messages; const finalResponse = response.messages[response.messages.length - 1]?.content; console.log(`Agent: ${finalResponse}\n`); rl.prompt(); }); rl.on('close', () => { console.log('\n👋 Session ended.'); process.exit(0); }); ``` ### 9. Run the application No description provided. ```python if __name__ == "__main__": asyncio.run(main()) ``` ```typescript main().catch((err) => { console.error('Fatal error:', err); process.exit(1); }); ``` ## Complete Code ```python from langchain_mcp_adapters.client import MultiServerMCPClient from langchain.agents import create_agent from dotenv import load_dotenv from composio import Composio import asyncio import os load_dotenv() async def main(): composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) if not os.getenv("COMPOSIO_API_KEY"): raise ValueError("COMPOSIO_API_KEY is not set") if not os.getenv("COMPOSIO_USER_ID"): raise ValueError("COMPOSIO_USER_ID is not set") session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['zerobounce'] ) url = session.mcp.url client = MultiServerMCPClient({ "zerobounce-agent": { "transport": "streamable_http", "url": url, "headers": { "x-api-key": os.getenv("COMPOSIO_API_KEY") } } }) tools = await client.get_tools() agent = create_agent("gpt-5", tools) conversation_history = [] print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Zerobounce related question or task to the agent.\n") while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue conversation_history.append({"role": "user", "content": user_input}) print("\nAgent is thinking...\n") response = await agent.ainvoke({"messages": conversation_history}) conversation_history = response['messages'] final_response = response['messages'][-1].content print(f"Agent: {final_response}\n") if __name__ == "__main__": asyncio.run(main()) ``` ```typescript import { Composio } from '@composio/core'; import { LangchainProvider } from '@composio/langchain'; import { MultiServerMCPClient } from "@langchain/mcp-adapters"; import { createAgent } from "langchain"; import * as readline from 'readline'; import 'dotenv/config'; const composioApiKey = process.env.COMPOSIO_API_KEY; const userId = process.env.COMPOSIO_USER_ID; if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set'); if (!userId) throw new Error('COMPOSIO_USER_ID is not set'); async function main() { const composio = new Composio({ apiKey: composioApiKey as string, provider: new LangchainProvider() }); const session = await composio.create( userId as string, { toolkits: ['zerobounce'] } ); const url = session.mcp.url; const client = new MultiServerMCPClient({ "zerobounce-agent": { transport: "http", url: url, headers: { "x-api-key": process.env.COMPOSIO_API_KEY } } }); const tools = await client.getTools(); const agent = createAgent({ model: "gpt-5", tools }); let conversationHistory: any[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log("Ask any Zerobounce related question or task to the agent.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: 'You: ' }); 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; } conversationHistory.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); const response = await agent.invoke({ messages: conversationHistory }); conversationHistory = response.messages; const finalResponse = response.messages[response.messages.length - 1]?.content; console.log(`Agent: ${finalResponse}\n`); rl.prompt(); }); rl.on('close', () => { console.log('\nSession ended.'); process.exit(0); }); } main().catch((err) => { console.error('Fatal error:', err); process.exit(1); }); ``` ## Conclusion You've successfully built a LangChain agent that can interact with Zerobounce through Composio's Tool Router. Key features of this implementation: - Dynamic tool loading through Composio's Tool Router - Conversation history maintenance for context-aware responses - Async Python provides clean, efficient execution of agent workflows You can extend this further by adding 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) - [Vercel AI SDK](https://composio.dev/toolkits/zerobounce/framework/ai-sdk) - [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 LangChain? Yes, you can. LangChain 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)