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How to integrate Apilio MCP with Pydantic AI

Connect Pydantic AI to Apilio MCP. List all boolean variables and their status, show me all your current logicblocks, and more using natural language, with authentication handled for you.

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Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations.

8 Tools

Introduction

This guide walks you through connecting Apilio to Pydantic AI using the Composio tool router. By the end, you'll have a working Apilio agent that can list your logicblocks, read variable values, check time and Tuya conditions, and review variable conditions through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Apilio account through Composio's Apilio MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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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 Apilio
  • 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 Apilio 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 Apilio MCP server, and what's possible with it?

The Apilio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Apilio account. It provides structured and secure access to your home automation setup, so your agent can inspect variables, retrieve conditions, review logicblocks, and list time and Tuya conditions on your behalf.

  • Variable monitoring: Have your agent fetch your boolean, numeric, and string variables to review their current values and available details.
  • Condition review: Let the agent retrieve all conditions configured in your Apilio account so you can understand your automation rules.
  • Logicblock inspection: Direct your agent to list your logicblocks and help you review how your home automations are organized.
  • Time condition lookup: Instruct your agent to fetch your time conditions when you need to check schedule-based automation logic.
  • Tuya and variable condition discovery: Have your agent list Tuya conditions and variable conditions used across your connected automation setup.

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 Apilio
  • 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 Apilio
  • MCPServerStreamableHTTP connects to the Apilio 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 Apilio
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["apilio"],
    )
    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 Apilio 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
apilio_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[apilio_mcp],
    instructions=(
        "You are a Apilio assistant. Use Apilio tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Apilio endpoint
  • The agent uses GPT-5 to interpret user commands and perform Apilio 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 Apilio.\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
  • Apilio 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 Apilio 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 Apilio
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["apilio"],
    )
    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
    apilio_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[apilio_mcp],
        instructions=(
            "You are a Apilio assistant. Use Apilio 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 Apilio.\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 Apilio through Composio's Tool Router. With this setup, your agent can perform real Apilio 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 + Apilio 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 Apilio action and event your agent gets out of the box.

Get Boolean Variables

Tool to fetch all boolean variables.

Get Conditions

Retrieves all conditions from your Apilio account.

Get Logicblocks

Retrieves all logicblocks for the authenticated Apilio user.

Get Numeric Variables

Retrieves all numeric variables from your Apilio account with their current values and metadata.

Get String Variables

Tool to fetch all string variables.

List Time Conditions

Tool to fetch all time conditions of a user.

List Tuya Conditions

Tool to retrieve all Tuya conditions from your Apilio account.

List Variable Conditions

Tool to retrieve all variable conditions from your Apilio account.

FRAMEWORKS

How to build Apilio MCP Agent with another framework

Claude Code logo

Claude Code

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Claude Cowork logo

Claude Cowork

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OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

Use Apilio MCP with Claude Agent SDK

Codex logo

Codex

Use Apilio MCP with Codex

OpenClaw logo

OpenClaw

Use Apilio MCP with OpenClaw

Hermes logo

Hermes

Use Apilio MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Apilio MCP with Atomic Agent

Google ADK logo

Google ADK

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LangChain logo

LangChain

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Vercel AI SDK logo

Vercel AI SDK

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Mastra AI logo

Mastra AI

Use Apilio MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Apilio MCP with LlamaIndex

CrewAI logo

CrewAI

Use Apilio MCP with CrewAI

AutoGen logo

AutoGen

Use Apilio MCP with AutoGen

FAQ

Frequently asked questions

With a standalone Apilio MCP server, the agents and LLMs can only access a fixed set of Apilio tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Apilio and many other apps based on the task at hand, all through a single MCP endpoint.

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 Apilio tools.

Yes, absolutely. You can configure which Apilio 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.

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 Apilio data and credentials are handled as safely as possible.

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