# How to integrate Breeze MCP with Autogen

```json
{
  "title": "How to integrate Breeze MCP with Autogen",
  "toolkit": "Breeze",
  "toolkit_slug": "breeze",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/breeze/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/breeze/framework/autogen.md",
  "updated_at": "2026-05-12T10:04:00.954Z"
}
```

## Introduction

This guide walks you through connecting Breeze to AutoGen using the Composio tool router. By the end, you'll have a working Breeze agent that can create a new workspace for the design team, add john and sara to project alpha, archive completed project called website redesign through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Breeze account through Composio's Breeze MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Breeze with

- [OpenAI Agents SDK](https://composio.dev/toolkits/breeze/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/breeze/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/breeze/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/breeze/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/breeze/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/breeze/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/breeze/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/breeze/framework/cli)
- [Google ADK](https://composio.dev/toolkits/breeze/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/breeze/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/breeze/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/breeze/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/breeze/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/breeze/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 Breeze
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Breeze tools
- Run a live chat loop where you ask the agent to perform Breeze 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 Breeze MCP server, and what's possible with it?

The Breeze MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Breeze account. It provides structured and secure access to your projects, tasks, and team collaboration features, so your agent can create projects, manage cards, add team members, organize workflows, and handle workspace administration on your behalf.
- Project creation and management: Instantly create new projects, archive completed ones, or delete projects you no longer need—keeping your workspace organized at all times.
- Task and card automation: Have your agent create, update, or delete cards (tasks) in any project, assign due dates, and manage assignees for seamless task tracking.
- Team and member collaboration: Easily add people to projects or remove them, ensuring the right teammates are always involved without manual overhead.
- Workflow structuring with lists: Let your agent create new stages (lists) within projects to tailor workflows and keep every team organized by process.
- Workspace setup and cleanup: Automate creation or deletion of workspaces to reflect your team’s evolving structure and simplify workspace administration.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BREEZE_ADD_PROJECT_PEOPLE` | Add Project People | Add people to a Breeze project by inviting them via email. This action invites one or more users to a project by their email addresses. The response returns the complete list of all users currently in the project (including the newly added ones). Use this when you need to give users access to a specific project. |
| `BREEZE_ARCHIVE_PROJECT` | Archive Project | Tool to archive a specific project. Use when you need to hide a completed or inactive project from active views after confirming its details. |
| `BREEZE_CREATE_CARD` | Create Card | Tool to create a new card in a project. Use after confirming the project_id. Creates a task with details like name, due date, and assignees. |
| `BREEZE_CREATE_LIST` | CREATE_LIST | Tool to create a new list (stage) in a Breeze project. Use when you've selected a project and need to add a new stage. Example: "Create a new Todo list for project 42." |
| `BREEZE_CREATE_PROJECT` | Create Project | Creates a new project in Breeze project management system. Use this action to initialize a new project with a given name. The newly created project will: - Be automatically assigned to the authenticated user as owner - Have default budget values set to 0 - Not be assigned to any workspace initially (can be configured later) - Not be archived by default Returns comprehensive project details including ID, timestamps, budget information, and user assignments. |
| `BREEZE_CREATE_WORKSPACE` | Create Workspace | Tool to create a new workspace. Use after deciding on the workspace name. |
| `BREEZE_DELETE_CARD` | Delete Card | Tool to delete a specific card (task) by its ID. Use when you need to remove a task permanently; deletions cannot be undone. |
| `BREEZE_DELETE_PROJECT` | Delete Project | Tool to delete a specific project by ID. Use when you need to remove a project after confirming its ID. |
| `BREEZE_DELETE_PROJECT_PERSON` | Delete Person from Project | Tool to delete a person from a project by user ID. Use after confirming the project and user details. Example: "Delete user 456 from project 123". |
| `BREEZE_DELETE_WORKSPACE` | Delete Workspace | Tool to delete a specific workspace by ID. Use when permanently removing a workspace after confirming the correct workspace ID. |
| `BREEZE_GET_CARD` | Get Card | Tool to retrieve detailed info for a specific card (task) in a project. Use when you know the project_id and card_id and need all metadata like tags, users, todos, and time entries. |
| `BREEZE_GET_CARDS` | GET_CARDS | Tool to get all cards (tasks) for a specific project. Use after confirming the project exists. Example: "List all cards in project 42." |
| `BREEZE_GET_PROJECT` | Get Project | Tool to get a specific project by ID. Use when you need detailed project information after confirming the project ID. Example: "Get project 123 details". |
| `BREEZE_GET_PROJECT_PEOPLE` | Get Project People | Tool to get all users in a project. Use when you have a valid project ID and need to list its users. |
| `BREEZE_GET_PROJECTS` | Get Projects | Retrieves a list of all active (non-archived) projects in Breeze. Returns comprehensive project details including budget, time tracking, assigned users, tags, and metadata. Use this action to: - Get an overview of all current projects - Find specific projects by browsing the list - Access project IDs for use with other project-related actions - Check project budgets, hours tracked, and team assignments Note: Only returns active projects. Use GET_ARCHIVED_PROJECTS to retrieve archived projects. |
| `BREEZE_GET_WORKSPACE` | Get Workspace | Tool to get a specific workspace by ID. Use when you need workspace details including projects after confirming the workspace ID. |
| `BREEZE_GET_WORKSPACES` | Get Workspaces | Tool to get all workspaces. Use when you need to list available workspaces for the authenticated user. |
| `BREEZE_MOVE_CARD` | Move Card | Tool to move a card to a different stage or position. Use after confirming stage_id and prev_id. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Breeze MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Breeze. Instead of manually wiring Breeze 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 Breeze 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 Breeze 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 Breeze 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 Breeze 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 Breeze session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["breeze"]
    )
    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 Breeze 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 Breeze assistant agent with MCP tools
    agent = AssistantAgent(
        name="breeze_assistant",
        description="An AI assistant that helps with Breeze 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 Breeze 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 Breeze 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 Breeze session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["breeze"]
    )
    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 Breeze assistant agent with MCP tools
        agent = AssistantAgent(
            name="breeze_assistant",
            description="An AI assistant that helps with Breeze 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 Breeze 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 Breeze 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 Breeze, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Breeze MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/breeze/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/breeze/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/breeze/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/breeze/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/breeze/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/breeze/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/breeze/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/breeze/framework/cli)
- [Google ADK](https://composio.dev/toolkits/breeze/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/breeze/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/breeze/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/breeze/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/breeze/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/breeze/framework/crew-ai)

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [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.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes.
- [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights.
- [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.
- [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.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Breeze MCP?

With a standalone Breeze MCP server, the agents and LLMs can only access a fixed set of Breeze tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Breeze 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 Breeze tools.

### Can I manage the permissions and scopes for Breeze while using Tool Router?

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
