# How to integrate Onesignal rest api MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Onesignal rest api MCP with Vercel AI SDK v6", "toolkit": "Onesignal rest api", "toolkit_slug": "onesignal_rest_api", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/onesignal_rest_api/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/onesignal_rest_api/framework/ai-sdk.md", "updated_at": "2026-05-12T10:20:40.184Z" } ``` ## Introduction This guide walks you through connecting Onesignal rest api to Vercel AI SDK v6 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 Vercel AI SDK 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) - [LangChain](https://composio.dev/toolkits/onesignal_rest_api/framework/langchain) - [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: - How to set up and configure a Vercel AI SDK agent with Onesignal rest api integration - Using Composio's Tool Router to dynamically load and access Onesignal rest api tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## 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 Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 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 required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client 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 mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Onesignal rest api-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["onesignal_rest_api"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Onesignal rest api tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to onesignal_rest_api, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Onesignal rest api tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript 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; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["onesignal_rest_api"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to onesignal_rest_api, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); 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; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Onesignal rest api agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom 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) - [LangChain](https://composio.dev/toolkits/onesignal_rest_api/framework/langchain) - [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) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. ## 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 Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)