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How to integrate Onesignal rest api MCP with Pydantic AI

Connect Pydantic AI to Onesignal rest api MCP. Send push notification to all active users, list all devices registered for your app, and more using natural language, with authentication handled for you.

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OneSignal is a cross-channel messaging platform offering REST APIs for notifications, user management, and app settings. It lets you reach users via push, email, and SMS from a single, unified interface.

15 Tools

Introduction

This guide walks you through connecting Onesignal rest api to Pydantic AI using the Composio tool router. By the end, you'll have a working Onesignal rest api agent that can send push notifications, create message templates, manage users and devices, view segments, and start live activities through natural language commands.

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

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

Also integrate Onesignal rest api with

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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 Onesignal rest api
  • 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 Onesignal rest api 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 Onesignal rest api MCP server, and what's possible with it?

The Onesignal rest api MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OneSignal account. It provides structured and secure access to your messaging platform, so your agent can perform actions like sending push notifications, managing devices, viewing app details, and segmenting audiences automatically on your behalf.

  • Automated push notifications and messaging: Instantly have your agent create and send targeted push notifications to your users, keeping them engaged and informed.
  • Device management and updates: Let your agent add, update, or remove registered devices (players) to keep your audience data fresh and accurate.
  • App insights and metadata retrieval: Effortlessly fetch and review detailed app information, notification history, and device lists for better operational visibility.
  • Audience segmentation and targeting: Enable your agent to view and utilize user segments, making it easy to target the right audience for every message.
  • Notification analytics and history: Have your agent retrieve past notifications, track delivery, and analyze engagement trends for continuous improvement.

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

Begin Live Activity

Tool to start a Live Activity on OneSignal.

Create Notification

Tool to create and send a OneSignal push notification.

Create Template

Tool to create reusable message templates for push, email, and SMS channels.

Create User

Create a OneSignal user with optional subscriptions and aliases, or modify subscriptions associated with an existing user.

Delete Alias

Tool to delete an alias by alias label from a OneSignal user.

Delete Device

Tool to delete a device (player) from a OneSignal app.

Fetch User Identity

Tool to retrieve all aliases for a user identified by a specific alias.

Get Eligible In-App Messages

Tool to retrieve the manifest of In-App Messages that a subscription is eligible to display.

Update Device

Tool to update properties of an existing device.

Update Subscription

Tool to update an existing subscription's properties.

View OneSignal App

Tool to retrieve metadata for a single OneSignal app.

View Device

Tool to retrieve details of a specific device (player).

View Devices

Tool to retrieve a paginated list of devices (players) for a OneSignal app.

View Notifications

Tool to retrieve details of multiple notifications.

View Segments

List segments associated with a OneSignal app, using limit and offset to page through results.

FRAMEWORKS

How to build Onesignal rest api MCP Agent with another framework

Claude Code logo

Claude Code

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Claude Cowork

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OpenAI Agents SDK logo

OpenAI Agents SDK

Use Onesignal rest api MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Onesignal rest api MCP with Claude Agent SDK

Codex logo

Codex

Use Onesignal rest api MCP with Codex

OpenClaw logo

OpenClaw

Use Onesignal rest api MCP with OpenClaw

Hermes logo

Hermes

Use Onesignal rest api MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Onesignal rest api MCP with Atomic Agent

Google ADK logo

Google ADK

Use Onesignal rest api MCP with Google ADK

LangChain logo

LangChain

Use Onesignal rest api MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Onesignal rest api MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Onesignal rest api MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Onesignal rest api MCP with LlamaIndex

CrewAI logo

CrewAI

Use Onesignal rest api MCP with CrewAI

AutoGen logo

AutoGen

Use Onesignal rest api MCP with AutoGen

FAQ

Frequently asked questions

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

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

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