# How to integrate Onesignal rest api MCP with LangChain

```json
{
  "title": "How to integrate Onesignal rest api MCP with LangChain",
  "toolkit": "Onesignal rest api",
  "toolkit_slug": "onesignal_rest_api",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/onesignal_rest_api/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/onesignal_rest_api/framework/langchain.md",
  "updated_at": "2026-05-12T10:20:40.184Z"
}
```

## Introduction

This guide walks you through connecting Onesignal rest api to LangChain using the Composio tool router. By the end, you'll have a working Onesignal rest api agent that can send push notification to all active users, list all devices registered for your app, view details of last 10 notifications through natural language commands.
This guide will help you understand how to give your LangChain 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

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Onesignal rest api project to Composio
- Create a Tool Router MCP session for Onesignal rest api
- Initialize an MCP client and retrieve Onesignal rest api tools
- Build a LangChain agent that can interact with Onesignal rest api
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ONESIGNAL_REST_API_BEGIN_LIVE_ACTIVITY` | Begin Live Activity | Tool to start a Live Activity on OneSignal. Use when you need to initiate a Live Activity session with a push token and subscription ID. |
| `ONESIGNAL_REST_API_CREATE_NOTIFICATION` | Create Notification | Tool to create and send a OneSignal push notification. Use when you have your message and target audience ready to dispatch notifications. |
| `ONESIGNAL_REST_API_CREATE_TEMPLATE` | Create Template | Tool to create reusable message templates for push, email, and SMS channels. Use when you need to create a template that can be accessed through both the dashboard and API using a template_id. |
| `ONESIGNAL_REST_API_CREATE_USER` | Create User | Tool to create a OneSignal user with optional subscriptions and aliases. Aliases provided in the payload will be used to look up an existing user. |
| `ONESIGNAL_REST_API_DELETE_ALIAS` | Delete Alias | Tool to delete an alias by alias label from a OneSignal user. Use when you need to remove a specific alias identity from a user's profile. |
| `ONESIGNAL_REST_API_DELETE_DEVICE` | Delete Device | Tool to delete a device (player) from a OneSignal app. Use when you need to remove a specific device by its player ID. |
| `ONESIGNAL_REST_API_FETCH_USER_IDENTITY` | Fetch User Identity | Tool to retrieve all aliases for a user identified by a specific alias. Use when you need to fetch the complete identity mapping for a OneSignal user. |
| `ONESIGNAL_REST_API_GET_ELIGIBLE_IAMS` | Get Eligible In-App Messages | Tool to retrieve the manifest of In-App Messages that a subscription is eligible to display. Use when you need to fetch eligible IAMs for a specific subscription. |
| `ONESIGNAL_REST_API_UPDATE_DEVICE` | Update Device | Tool to update properties of an existing device. Use when you need to modify device attributes after registration. |
| `ONESIGNAL_REST_API_UPDATE_SUBSCRIPTION` | Update Subscription | Tool to update an existing subscription's properties. Use when you need to modify subscription attributes like token, enabled status, or device information. |
| `ONESIGNAL_REST_API_VIEW_AN_APP` | View OneSignal App | Tool to retrieve metadata for a single OneSignal app. Use when you need to fetch app details by its ID. |
| `ONESIGNAL_REST_API_VIEW_DEVICE` | View Device | Tool to retrieve details of a specific device (player). Use when you have a OneSignal player_id and need current device info. |
| `ONESIGNAL_REST_API_VIEW_DEVICES` | View Devices | Tool to retrieve a paginated list of devices (players) for a OneSignal app. Use when you need to list or audit all registered devices for a given app. |
| `ONESIGNAL_REST_API_VIEW_NOTIFICATIONS` | View Notifications | Tool to retrieve details of multiple notifications. Use when you need to list notifications for a specific app. |
| `ONESIGNAL_REST_API_VIEW_SEGMENTS` | View Segments | Tool to view segments for a OneSignal app. Use when you need to list all segments associated with an app. |

## Supported Triggers

None listed.

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

The Onesignal rest api MCP server is an implementation of the Model Context Protocol that connects your AI agent to Onesignal rest api. It provides structured and secure access so your agent can perform Onesignal rest api 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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Onesignal rest api tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

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
- This approach allows the agent to dynamically load and use Onesignal rest api tools as needed
```python
# Create Tool Router session for Onesignal rest api
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['onesignal_rest_api']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['onesignal_rest_api']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "onesignal_rest_api-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "onesignal_rest_api-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Onesignal rest api related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Onesignal rest api related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['onesignal_rest_api']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "onesignal_rest_api-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Onesignal rest api related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['onesignal_rest_api']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "onesignal_rest_api-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Onesignal rest api related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Onesignal rest api through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## How to build Onesignal rest api MCP Agent with another framework

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

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Onesignal rest api MCP?

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.

### Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain 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.

### Can I manage the permissions and scopes for Onesignal rest api while using Tool Router?

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.

### 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 Onesignal rest api data and credentials are handled as safely as possible.

---
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