# How to integrate Pushbullet MCP with Autogen ```json { "title": "How to integrate Pushbullet MCP with Autogen", "toolkit": "Pushbullet", "toolkit_slug": "pushbullet", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/pushbullet/framework/autogen", "markdown_url": "https://composio.dev/toolkits/pushbullet/framework/autogen.md", "updated_at": "2026-05-12T10:23:03.526Z" } ``` ## Introduction This guide walks you through connecting Pushbullet to AutoGen 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 AutoGen 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) - [Vercel AI SDK](https://composio.dev/toolkits/pushbullet/framework/ai-sdk) - [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: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Pushbullet - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Pushbullet tools - Run a live chat loop where you ask the agent to perform Pushbullet operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## 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 agents and assistants directly to Pushbullet. Instead of manually wiring Pushbullet APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Pushbullet account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Pushbullet via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Pushbullet connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Pushbullet tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Pushbullet session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["pushbullet"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Pushbullet tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Pushbullet assistant agent with MCP tools agent = AssistantAgent( name="pushbullet_assistant", description="An AI assistant that helps with Pushbullet operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Pushbullet tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Pushbullet related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Pushbullet session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["pushbullet"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Pushbullet assistant agent with MCP tools agent = AssistantAgent( name="pushbullet_assistant", description="An AI assistant that helps with Pushbullet operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Pushbullet related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Pushbullet through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Pushbullet, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## 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) - [Vercel AI SDK](https://composio.dev/toolkits/pushbullet/framework/ai-sdk) - [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 Autogen? Yes, you can. Autogen 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)