# How to integrate Neverbounce MCP with Pydantic AI ```json { "title": "How to integrate Neverbounce MCP with Pydantic AI", "toolkit": "Neverbounce", "toolkit_slug": "neverbounce", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/neverbounce/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/neverbounce/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:20:05.703Z" } ``` ## Introduction This guide walks you through connecting Neverbounce to Pydantic AI 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 Pydantic AI 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) - [Vercel AI SDK](https://composio.dev/toolkits/neverbounce/framework/ai-sdk) - [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 your Composio API key and User ID - How to create a Composio Tool Router session for Neverbounce - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Neverbounce workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 starting, make sure you have: - Python 3.9 or higher - A Composio account with an active API key - Basic familiarity with Python and async programming ### 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 Install the required libraries. What's happening: - composio connects your agent to external SaaS tools like Neverbounce - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Neverbounce - MCPServerStreamableHTTP connects to the Neverbounce MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session 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 session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Neverbounce composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["neverbounce"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Neverbounce endpoint - The agent uses GPT-5 to interpret user commands and perform Neverbounce operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent neverbounce_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[neverbounce_mcp], instructions=( "You are a Neverbounce assistant. Use Neverbounce tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Neverbounce API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Neverbounce.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Neverbounce composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["neverbounce"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent neverbounce_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[neverbounce_mcp], instructions=( "You are a Neverbounce assistant. Use Neverbounce tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Neverbounce.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Neverbounce through Composio's Tool Router. With this setup, your agent can perform real Neverbounce actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Neverbounce for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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) - [Vercel AI SDK](https://composio.dev/toolkits/neverbounce/framework/ai-sdk) - [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 Pydantic AI? Yes, you can. Pydantic AI 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)