How to integrate Blooio MCP with Autogen

This guide walks you through connecting Blooio to AutoGen using the Composio tool router. By the end, you'll have a working Blooio agent that can review your chats, create contacts, tag contacts, manage groups, and check poll results through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Blooio account through Composio's Blooio MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Blooio logoBlooio
Api Key

Blooio is a stable v2 API platform for messaging, chats, contacts, groups, phone numbers, and account analytics. It gives teams a clean way to build reliable communication workflows without stitching together fragile custom APIs.

26 Tools

Introduction

This guide walks you through connecting Blooio to AutoGen using the Composio tool router. By the end, you'll have a working Blooio agent that can review your chats, create contacts, tag contacts, manage groups, and check poll results through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Blooio account through Composio's Blooio MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Blooio with

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 Blooio
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Blooio tools
  • Run a live chat loop where you ask the agent to perform Blooio 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 Blooio MCP server, and what's possible with it?

The Blooio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Blooio account. It provides structured and secure access to your messages, chats, contacts, groups, phone numbers, and account insights, so your agent can send messages, manage conversations, organize contacts, coordinate groups, and review account activity on your behalf.

  • Messaging and interactive polls: Have your agent send text, attachments, replies, or native iMessage polls, check delivery details, and review poll results.
  • Chat and reaction management: Let the agent find conversations, review message history, mark chats as read, and add or remove reactions from messages.
  • Contact organization: Direct your agent to create, find, update, or delete contacts, manage their tags, and check whether they can receive iMessage, SMS, or FaceTime.
  • Messaging group coordination: Instruct your agent to create, find, rename, or delete messaging groups and review their members.
  • Account and sender oversight: Have your agent review your organization, assigned devices, message usage, available sender numbers, and fleet risk summary.

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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Blooio account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Blooio via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 Blooio connections to use
5

Import dependencies and create Tool Router session

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 Blooio session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["blooio"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Blooio tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

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")}
)

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
7

Create the model client and agent

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 Blooio assistant agent with MCP tools
    agent = AssistantAgent(
        name="blooio_assistant",
        description="An AI assistant that helps with Blooio operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Blooio tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Blooio 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Blooio 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

Complete Code

Here's the complete code to get you started with Blooio and AutoGen:

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 Blooio session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["blooio"]
    )
    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 Blooio assistant agent with MCP tools
        agent = AssistantAgent(
            name="blooio_assistant",
            description="An AI assistant that helps with Blooio 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 Blooio 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 Blooio 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 Blooio, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Add Contact Tags

Add or reactivate one or more free-form tags on a contact.

Create Contact

Create a contact from an E.

Create Group

Create a messaging group, optionally linking an existing iMessage chat and recording its members; new contacts may be created for unknown members.

Delete Contact

Soft-delete one contact identified by E.

Delete Group

Soft-delete a group, remove its members, and exit its linked iMessage chat when one exists.

Get Account

Return the authenticated organization, assigned devices, and message usage without exposing the API-key identifier.

Get Chat

Return detailed counts, participant context, and latest-message metadata for one conversation.

Get Contact

Return one contact by E.

Get Contact Capabilities

Check whether a contact can receive iMessage, SMS, or FaceTime before choosing a communication path.

Get Group

Return one messaging group by its grp_ identifier.

Get Message

Return one message with content, reactions, delivery status, protocol, errors, and inline-reply context.

Get Poll Results

Return a poll's definition, option vote counts, and total votes.

Get Risk Summary

Return the cached fleet risk rollup.

List Chats

Search and page through conversations, ordered by recent activity or oldest activity.

List Contacts

Search and page through organization contacts by identifier or name.

List Group Members

Page through the members recorded for a messaging group.

List Groups

Search and page through messaging groups by name.

List Messages

Page through messages in one chat with direction, time-window, and ordering filters.

List Numbers

List sender phone numbers assigned to the connected API key and their availability state.

Mark Chat Read

Mark every message in a chat as read and irreversibly send an externally visible read receipt to the sender; the receipt cannot be unsent.

Remove Contact Tags

Soft-delete one or more exact tags from a contact sequentially; if a later removal fails, earlier removals remain applied.

Send Message

Irreversibly send one or multiple text, attachment, multipart, or inline-reply messages; multi-recipient sends may create or reuse an unnamed group and may incur messaging charges.

Send Poll

Irreversibly send an interactive native iMessage poll to a chat.

Set Message Reaction

Add or remove a classic tapback or emoji reaction on a specific or relative message in a chat.

Update Contact

Set or clear the display name of an existing contact.

Update Group

Rename a group and, when linked, synchronize the new name to its iMessage chat.

FAQ

Frequently asked questions

With a standalone Blooio MCP server, the agents and LLMs can only access a fixed set of Blooio tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Blooio and many other apps based on the task at hand, all through a single MCP endpoint.

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 Blooio tools.

Yes, absolutely. You can configure which Blooio 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 Blooio data and credentials are handled as safely as possible.

Start with Blooio.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Blooio tool your agent needs.Free to start.

Start building