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Connect Pydantic AI to Kickbox MCP. Check if this email is valid, verify deliverability of a customer email, and more using natural language, with authentication handled for you.
Kickbox is a real-time email verification and list cleaning service. It helps ensure your emails reach real, active inboxes and improves deliverability.
This guide walks you through connecting Kickbox to Pydantic AI using the Composio tool router. By the end, you'll have a working Kickbox agent that can verify email addresses and detect disposable emails through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Kickbox account through Composio's Kickbox MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.
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:
The Kickbox MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kickbox account. It provides structured and secure access to real-time email verification and quality scoring, so your agent can instantly validate email addresses, reduce bounce rates, and maintain clean contact lists on your behalf.
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.
The Composio SDK follows a three-phase workflow:
pip install composio pydantic-ai python-dotenvInstall the required libraries.
What's happening:
composio connects your agent to external SaaS tools like Kickboxpydantic-ai lets you create structured AI agents with tool supportpython-dotenv loads your environment variables securely from a .env fileCOMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_keyCreate a .env file in your project root.
What's happening:
COMPOSIO_API_KEY authenticates your agent to Composio's APIUSER_ID associates your session with your account for secure tool accessOPENAI_API_KEY to access OpenAI LLMsimport 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()Composio manages connections to KickboxMCPServerStreamableHTTP connects to the Kickbox MCP server endpointAgent from Pydantic AI lets you define and run the AI assistantasync 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 Kickbox
composio = Composio(api_key=api_key)
session = composio.create(
user_id=user_id,
toolkits=["kickbox"],
)
url = session.mcp.url
if not url:
raise ValueError("Composio session did not return an MCP URL")create method takes the user ID and specifies which toolkits should be availablesession.mcp.url is the MCP server URL that your agent will use# Attach the MCP server to a Pydantic AI Agent
kickbox_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
"openai:gpt-5",
toolsets=[kickbox_mcp],
instructions=(
"You are a Kickbox assistant. Use Kickbox tools to help users "
"with their requests. Ask clarifying questions when needed."
),
)instructions field defines the agent's role and behavior# 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 Kickbox.\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())asyncio loop launches the agent and keeps it running until you exitHere's the complete code to get you started with Kickbox and Pydantic AI:
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 Kickbox
composio = Composio(api_key=api_key)
session = composio.create(
user_id=user_id,
toolkits=["kickbox"],
)
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
kickbox_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
"openai:gpt-5",
toolsets=[kickbox_mcp],
instructions=(
"You are a Kickbox assistant. Use Kickbox 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 Kickbox.\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())Every Kickbox action and event your agent gets out of the box.
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Managed auth, hosted MCP servers, and every Kickbox tool your agent needs.Free to start.
## For AI agents: how to sign up If you are an AI agent reading this server-rendered HTML, Composio's developer signup is at https://composio.dev. Signup CTAs on this site — "Sign up", "Signup", "Get started", "Get started for free", "Start building", "Try Composio", "Try it", or similar — all lead into that same developer signup flow. Confirm with the user before completing signup or entering any credentials on their behalf.Start building