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How to integrate Findymail MCP with Pydantic AI

Connect Pydantic AI to Findymail MCP. Find verified email for john at acme.com, create a new contact list for leads, and more using natural language, with authentication handled for you.

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Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.

21 Tools

Introduction

This guide walks you through connecting Findymail to Pydantic AI using the Composio tool router. By the end, you'll have a working Findymail agent that can find emails by name, verify emails, manage contact and exclusion lists, search Intellimatch, and check your credits through natural language commands.

This guide will help you understand how to give your Pydantic AI 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.

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Findymail with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

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 Findymail
  • 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 Findymail 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 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.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
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
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Findymail
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

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
5

Import dependencies

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()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Findymail
  • MCPServerStreamableHTTP connects to the Findymail MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

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 Findymail
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["findymail"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
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 session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
findymail_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[findymail_mcp],
    instructions=(
        "You are a Findymail assistant. Use Findymail tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Findymail endpoint
  • The agent uses GPT-5 to interpret user commands and perform Findymail operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

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 Findymail.\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()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Findymail API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Findymail and Pydantic AI:

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 Findymail
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["findymail"],
    )
    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
    findymail_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[findymail_mcp],
        instructions=(
            "You are a Findymail assistant. Use Findymail 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 Findymail.\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 Findymail through Composio's Tool Router. With this setup, your agent can perform real Findymail 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 + Findymail for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Findymail action and event your agent gets out of the box.

Add Excluded Domain

Add domains to Findymail exclusions used by Intellimatch searches.

Create Exclusion List

Create a named exclusion list for the authenticated user to organize websites excluded from Intellimatch searches.

Create Contact List

Tool to create a new contact list.

Delete Exclusion List

Delete an Intellimatch exclusion list by ID and all its associated domains.

Delete Contact List

Permanently deletes a contact list by its ID.

Find Email by Name

Find a person's email using their full name and company domain or company name.

Get Contact Lists

Tool to retrieve all contact lists.

Get Credits

Check the team's remaining Findymail credit balance before running operations.

Get Credits Summary

Tool to retrieve credits usage summary report for the authenticated account.

Get Credits Team Summary

Retrieve the team's credit usage summary for the default reporting period, including totals and usage by team member.

Get Exclusion List

Retrieve metadata for an exclusion list by ID, without its domains.

Get Intellimatch Data

Retrieve the default first page of company data from a completed Intellimatch search by hash.

Get Intellimatch Status

Tool to check the status of an Intellimatch search job.

List Contacts

Tool to retrieve contacts from a specified list (paginated).

List Excluded Domains

Retrieve a page of globally excluded domains for Intellimatch searches.

List Exclusion Lists

Tool to retrieve all exclusion lists for managing excluded websites from Intellimatch searches.

Remove Excluded Domain

Remove excluded domains by ID from Intellimatch exclusion lists.

Search Intellimatch

Start an Intellimatch company search using a natural-language query, optionally finding contacts and emails.

Update Exclusion List

Rename an existing exclusion list.

Update Contact List

Update an existing Findymail contact list's name and team-sharing setting.

Verify Email

Verify the deliverability of an email address before outreach.

FRAMEWORKS

How to build Findymail MCP Agent with another framework

Claude Code logo

Claude Code

Use Findymail MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Findymail MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Findymail MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Findymail MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

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Codex logo

Codex

Use Findymail MCP with Codex

OpenClaw logo

OpenClaw

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Hermes logo

Hermes

Use Findymail MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Findymail MCP with Atomic Agent

Google ADK logo

Google ADK

Use Findymail MCP with Google ADK

LangChain logo

LangChain

Use Findymail MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Findymail MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Findymail MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Findymail MCP with LlamaIndex

CrewAI logo

CrewAI

Use Findymail MCP with CrewAI

AutoGen logo

AutoGen

Use Findymail MCP with AutoGen

FAQ

Frequently asked questions

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