# How to integrate Emaillistverify MCP with Pydantic AI

```json
{
  "title": "How to integrate Emaillistverify MCP with Pydantic AI",
  "toolkit": "Emaillistverify",
  "toolkit_slug": "emaillistverify",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/emaillistverify/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/emaillistverify/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:10:14.160Z"
}
```

## Introduction

This guide walks you through connecting Emaillistverify to Pydantic AI using the Composio tool router. By the end, you'll have a working Emaillistverify agent that can check if this email address is valid, get detailed deliverability info for an email, verify a user's email before signup through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Emaillistverify account through Composio's Emaillistverify MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Emaillistverify with

- [OpenAI Agents SDK](https://composio.dev/toolkits/emaillistverify/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/emaillistverify/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/emaillistverify/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/emaillistverify/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/emaillistverify/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/emaillistverify/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/emaillistverify/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/emaillistverify/framework/cli)
- [Google ADK](https://composio.dev/toolkits/emaillistverify/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/emaillistverify/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/emaillistverify/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/emaillistverify/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/emaillistverify/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/emaillistverify/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 Emaillistverify
- 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 Emaillistverify 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 Emaillistverify MCP server, and what's possible with it?

The Emaillistverify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Emaillistverify account. It provides structured and secure access to your email verification tools, so your agent can validate addresses, check deliverability, and provide detailed insights into email list quality on your behalf.
- Real-time email verification: Instantly check if a single email address is valid and deliverable before adding it to your list or sending messages.
- Detailed email validation insights: Get in-depth reports on why an email address may be risky or undeliverable, including error types and validation reasons.
- Automated list hygiene: Quickly verify new signups or leads as they come in, helping you keep your email lists clean and up-to-date.
- Prevent bounced emails: Reduce hard bounces and protect your sender reputation by validating addresses before campaigns are sent.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `EMAILLISTVERIFY_CHECK_BLACKLISTS` | Check Blacklists | Tool to check an IP address (IPv4/IPv6) or domain against multiple DNS-based blacklists (DNSBLs) for spam or malicious activity. Use when you need to verify the reputation of an IP or domain. Rate limit: 10 requests/second. |
| `EMAILLISTVERIFY_CHECK_DISPOSABLE` | Check Disposable Domain | Tool to verify if an email domain is associated with temporary/disposable email addresses. Includes DNS record verification. Use when you need to validate if a domain is disposable before accepting email registrations. |
| `EMAILLISTVERIFY_DELETE_MAILLIST` | Delete Maillist | Tool to delete a finished email list. Use when you need to remove a completed verification list. Only lists that have completed verification can be deleted. |
| `EMAILLISTVERIFY_DOWNLOAD_MAILLIST` | Download Email List | Tool to download a finished email list with verification results. Supports customizable columns (firstName, lastName, gender, result, etc.) and file format (csv/xlsx). Rate limit: 5 requests/second. |
| `EMAILLISTVERIFY_FIND_CONTACT` | Find Contact Email | Tool to search for a contact's business email address by name and company domain. Returns possible emails with confidence levels (high/medium/low/unknown). Rate limit: 5 requests/second. Credits: 5 (with name) or 10 (domain only). |
| `EMAILLISTVERIFY_GET_API_FILE_INFO` | Get API File Info | Tool to retrieve progress of an uploaded email list verification. Returns status (errored/waiting/progress/finished) with download URLs when complete. |
| `EMAILLISTVERIFY_GET_CREDITS` | Get Credits | Tool to retrieve details about available on-demand and subscription credits. Use when you need to check credit balance before performing verifications. On-demand credits never expire, subscription credits are refreshed daily. Rate limit: 10 requests/second. |
| `EMAILLISTVERIFY_GET_EMAIL_JOB` | Get Email Job Status | Tool to get the status of an asynchronous email verification job. Use when you need to check if a verification job has completed and retrieve its results. Rate limit: 100 requests per second. |
| `EMAILLISTVERIFY_GET_MAILLIST_PROGRESS` | Get Maillist Progress | Tool to retrieve real-time progress updates for an uploaded email list verification. Shows status, completion percentage, and credit usage. Rate limit: 100 requests/second. |
| `EMAILLISTVERIFY_UPLOAD_EMAIL_LIST` | Upload Email List | Tool to upload an email list file for bulk verification. Accepts .csv, .txt, or .xlsx files (max 100MB, 1M rows). Returns an ID to query verification progress. Rate limit: 5 requests/second. |
| `EMAILLISTVERIFY_VERIFY_SINGLE_EMAIL` | Verify Single Email | Tool to verify email deliverability status of a single email address. Returns a plain text status representing deliverability. Rate limit: 10 requests/second. Credits required: 1. |
| `EMAILLISTVERIFY_VERIFY_SINGLE_EMAIL_DETAILED` | Verify Single Email Detailed | Tool to verify email deliverability with detailed metadata including MX server info, ESP, first/last name estimation, gender, and role detection. Use when you need comprehensive email validation beyond basic deliverability. Rate limit: 10 requests/second, requires 1 credit per verification. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Emaillistverify MCP server is an implementation of the Model Context Protocol that connects your AI agent to Emaillistverify. It provides structured and secure access so your agent can perform Emaillistverify 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 Emaillistverify
- 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 Emaillistverify
- MCPServerStreamableHTTP connects to the Emaillistverify 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 Emaillistverify 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 Emaillistverify
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["emaillistverify"],
    )
    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 Emaillistverify endpoint
- The agent uses GPT-5 to interpret user commands and perform Emaillistverify operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
emaillistverify_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[emaillistverify_mcp],
    instructions=(
        "You are a Emaillistverify assistant. Use Emaillistverify 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
- Emaillistverify 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 Emaillistverify.\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 Emaillistverify
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["emaillistverify"],
    )
    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
    emaillistverify_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[emaillistverify_mcp],
        instructions=(
            "You are a Emaillistverify assistant. Use Emaillistverify 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 Emaillistverify.\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 Emaillistverify through Composio's Tool Router. With this setup, your agent can perform real Emaillistverify 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 + Emaillistverify 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 Emaillistverify MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/emaillistverify/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/emaillistverify/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/emaillistverify/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/emaillistverify/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/emaillistverify/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/emaillistverify/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/emaillistverify/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/emaillistverify/framework/cli)
- [Google ADK](https://composio.dev/toolkits/emaillistverify/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/emaillistverify/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/emaillistverify/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/emaillistverify/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/emaillistverify/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/emaillistverify/framework/crew-ai)

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Emaillistverify MCP?

With a standalone Emaillistverify MCP server, the agents and LLMs can only access a fixed set of Emaillistverify tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Emaillistverify 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 Emaillistverify tools.

### Can I manage the permissions and scopes for Emaillistverify while using Tool Router?

Yes, absolutely. You can configure which Emaillistverify 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 Emaillistverify data and credentials are handled as safely as possible.

---
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