# How to integrate Pushbullet MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Pushbullet MCP with Vercel AI SDK v6", "toolkit": "Pushbullet", "toolkit_slug": "pushbullet", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/pushbullet/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/pushbullet/framework/ai-sdk.md", "updated_at": "2026-05-12T10:23:03.526Z" } ``` ## Introduction This guide walks you through connecting Pushbullet to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Pushbullet agent that can send a note to your phone right now, list all devices linked to your account, share this pdf with your laptop through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Pushbullet account through Composio's Pushbullet MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Pushbullet with - [OpenAI Agents SDK](https://composio.dev/toolkits/pushbullet/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/pushbullet/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/pushbullet/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/pushbullet/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/pushbullet/framework/codex) - [OpenClaw](https://composio.dev/toolkits/pushbullet/framework/openclaw) - [Hermes](https://composio.dev/toolkits/pushbullet/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/pushbullet/framework/cli) - [Google ADK](https://composio.dev/toolkits/pushbullet/framework/google-adk) - [LangChain](https://composio.dev/toolkits/pushbullet/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/pushbullet/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/pushbullet/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/pushbullet/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Pushbullet integration - Using Composio's Tool Router to dynamically load and access Pushbullet 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 Pushbullet MCP server, and what's possible with it? The Pushbullet MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Pushbullet account. It provides structured and secure access to your Pushbullet devices, chats, and pushes, so your agent can perform actions like sending notifications, sharing files, managing chats, and organizing devices on your behalf. - Instant push notifications and file sharing: Instruct your agent to send notes, links, or files to any connected device, user, or channel for seamless cross-device updates. - Device management and registration: Let your agent list, register, or remove devices from your Pushbullet account to keep your ecosystem up to date. - Chat creation and management: Have your agent create new chat threads, list ongoing conversations, or delete chats as needed for streamlined communication. - Bulk push and chat cleanup: Direct your agent to delete individual pushes, clear all pushes at once, or remove old chats and devices to keep your space organized. - User profile access and verification: Enable your agent to retrieve your current Pushbullet user profile, ensuring secure and accurate operations every time. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `PUSHBULLET_CREATE_CHAT` | Create Chat | Tool to create a new chat with the specified email address. Use when you need to initiate a conversation thread by email. | | `PUSHBULLET_CREATE_DEVICE` | Register Device | Tool to register a new device under the current user's account. Use when adding a new hardware or app device to Pushbullet. | | `PUSHBULLET_CREATE_PUSH` | Create Push | Tool to send a new push (note, link, or file) to a device, user, channel, or client. Use when you need to share content to a specific target. Example: "Send a link to https://example.com to device abc123". | | `PUSHBULLET_DELETE_ALL_PUSHES` | Delete All Pushes | Tool to delete all pushes for the current user asynchronously. Use when you need to bulk-clear all existing pushes in one call. | | `PUSHBULLET_DELETE_CHAT` | Delete Chat | Tool to delete a chat by its identifier. Use when you need to remove a chat from your Pushbullet account after confirming its identifier. | | `PUSHBULLET_DELETE_DEVICE` | Delete Pushbullet Device | Tool to remove a device by its identifier. Use when you need to delete a device from your Pushbullet account after confirming its identifier. | | `PUSHBULLET_DELETE_PUSH` | Delete Push | Tool to delete a specific push by its identifier. Use when you need to remove a push after confirming its identifier. | | `PUSHBULLET_GET_USER` | Get current user | Tool to retrieve the currently authenticated user's profile. Use when you need to verify the access token or display the current user's details. | | `PUSHBULLET_LIST_CHATS` | List Chats | Tool to list all chat objects for the current user. Use when you need the full set of chat threads before sending or muting messages. | | `PUSHBULLET_LIST_DEVICES` | List Devices | Tool to list all registered devices for the current user. Use after obtaining a valid access token. | | `PUSHBULLET_LIST_PUSHES` | List Pushes | Tool to list pushes with optional filtering and pagination. Use when retrieving or syncing pushes after a certain time. | | `PUSHBULLET_UPDATE_CHAT` | Mute or Unmute Chat | Tool to mute or unmute an existing chat. Use when adjusting notification settings for a specific chat by its identifier. | | `PUSHBULLET_UPDATE_DEVICE` | Update Device | Tool to update metadata for a device by its identifier. Use when changing a device's nickname, model, or other settings. | | `PUSHBULLET_UPDATE_PUSH` | Update Push | Tool to update a push (dismiss or modify list items) by its identifier. Use when marking a push as dismissed or updating list push items. | | `PUSHBULLET_UPLOAD_REQUEST` | Upload Request | Tool to obtain a signed upload URL for a file before pushing. Use when you need to upload file content via the signed S3 form data. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Pushbullet MCP server is an implementation of the Model Context Protocol that connects your AI agent to Pushbullet. It provides structured and secure access so your agent can perform Pushbullet 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 Pushbullet 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 Pushbullet-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: ["pushbullet"], }); 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 Pushbullet 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 pushbullet, 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 Pushbullet 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: ["pushbullet"], }); 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 pushbullet, 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 Pushbullet 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 Pushbullet MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/pushbullet/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/pushbullet/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/pushbullet/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/pushbullet/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/pushbullet/framework/codex) - [OpenClaw](https://composio.dev/toolkits/pushbullet/framework/openclaw) - [Hermes](https://composio.dev/toolkits/pushbullet/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/pushbullet/framework/cli) - [Google ADK](https://composio.dev/toolkits/pushbullet/framework/google-adk) - [LangChain](https://composio.dev/toolkits/pushbullet/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/pushbullet/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/pushbullet/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/pushbullet/framework/crew-ai) ## Related Toolkits - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. - [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management. - [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place. - [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action. - [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication. - [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack. - [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers. - [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Chatwork](https://composio.dev/toolkits/chatwork) - Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity. - [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease. - [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace. - [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms. - [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates. - [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices. - [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels. - [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks. - [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission. - [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security. - [Google Meet](https://composio.dev/toolkits/googlemeet) - Google Meet is a secure video conferencing platform for virtual meetings, chat, and screen sharing. It helps teams connect, collaborate, and communicate seamlessly from anywhere. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Pushbullet MCP? With a standalone Pushbullet MCP server, the agents and LLMs can only access a fixed set of Pushbullet tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Pushbullet 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 Pushbullet tools. ### Can I manage the permissions and scopes for Pushbullet while using Tool Router? Yes, absolutely. You can configure which Pushbullet 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 Pushbullet data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)