How to integrate Pushbullet MCP with CrewAI

This guide walks you through connecting Pushbullet to CrewAI 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 CrewAI 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.

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Pushbullet is a notification and file sharing service for devices and browsers. It helps you instantly send messages, files, and links between your devices and contacts.

15 Tools

Introduction

This guide walks you through connecting Pushbullet to CrewAI 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 CrewAI 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 SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Pushbullet connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Pushbullet
  • Build a conversational loop where your agent can execute Pushbullet operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Pushbullet connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Pushbullet via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Pushbullet MCP URL
6

Create a Composio Tool Router session for Pushbullet

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["pushbullet"])

url = session.mcp.url
What's happening:
  • You create a Pushbullet only session through Composio
  • Composio returns an MCP HTTP URL that exposes Pushbullet tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Pushbullet and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["pushbullet"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Pushbullet through Composio's Tool Router. The agent can perform Pushbullet operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

Every Pushbullet action and event your agent gets out of the box.

Create Chat

Tool to create a new chat with the specified email address.

Register Device

Tool to register a new device under the current user's account.

Create Push

Tool to send a new push (note, link, or file) to a device, user, channel, or client.

Delete All Pushes

Tool to delete all pushes for the current user asynchronously.

Delete Chat

Tool to delete a chat by its identifier.

Delete Pushbullet Device

Tool to remove a device by its identifier.

Delete Push

Tool to delete a specific push by its identifier.

Get current user

Tool to retrieve the currently authenticated user's profile.

List Chats

Tool to list all chat objects for the current user.

List Devices

Tool to list all registered devices for the current user.

List Pushes

Tool to list pushes with optional filtering and pagination.

Mute or Unmute Chat

Tool to mute or unmute an existing chat.

Update Device

Tool to update metadata for a device by its identifier.

Update Push

Tool to update a push (dismiss or modify list items) by its identifier.

Upload Request

Tool to obtain a signed upload URL for a file before pushing.

FRAMEWORKS

How to build Pushbullet MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Pushbullet MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Pushbullet MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Pushbullet MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Pushbullet MCP with Claude Cowork

Codex logo

Codex

Use Pushbullet MCP with Codex

OpenClaw logo

OpenClaw

Use Pushbullet MCP with OpenClaw

Hermes logo

Hermes

Use Pushbullet MCP with Hermes

CLI logo

CLI

Use Pushbullet MCP with CLI

Google ADK logo

Google ADK

Use Pushbullet MCP with Google ADK

LangChain logo

LangChain

Use Pushbullet MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Pushbullet MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Pushbullet MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Pushbullet MCP with LlamaIndex

FAQ

Frequently asked questions

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.

Yes, you can. CrewAI 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.

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.

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.

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