# How to integrate Attio MCP with Autogen

```json
{
  "title": "How to integrate Attio MCP with Autogen",
  "toolkit": "Attio",
  "toolkit_slug": "attio",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/attio/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/attio/framework/autogen.md",
  "updated_at": "2026-05-06T08:01:42.701Z"
}
```

## Introduction

This guide walks you through connecting Attio to AutoGen using the Composio tool router. By the end, you'll have a working Attio agent that can add a meeting note to john smith’s record, find all companies added this week, list recent notes for acme corp through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Attio account through Composio's Attio MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Attio with

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

The Attio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Attio account. It provides structured and secure access to your team’s relationship and workflow data, so your agent can perform actions like creating records, managing notes, searching your CRM, and organizing lists on your behalf.
- Automated record management: Effortlessly create, update, or permanently delete records for people, companies, deals, and more in your Attio workspace.
- Smart note taking and retrieval: Let your agent create, list, or delete notes attached to any record, keeping important context and meeting details organized for your team.
- Powerful object and list navigation: Retrieve and explore all available objects or lists within your workspace, making it easy for your AI to understand and organize your CRM structure.
- Advanced record search and filtering: Find specific CRM records either by unique ID or by searching with custom attributes, ensuring your agent surfaces the right data when you need it.
- Comprehensive workspace insight: Get detailed information about object types and their attributes, so your AI-powered workflows always use the right fields and relationships.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ATTIO_CREATE_NOTE` | Create Note | This tool creates a new note on a given record in attio. the note can be attached to any record type (like person, company, or deal) and includes a title and content. it requires parameters such as parent object, parent record id, title, and content, with an optional created at timestamp. |
| `ATTIO_CREATE_RECORD` | Create Record | This tool creates a new record in attio for a specified object type (people, companies, deals, users, workspaces, etc.). it requires the object type and a values dictionary containing the attributes for the new record. |
| `ATTIO_DELETE_NOTE` | Delete Note | This tool allows users to delete a specific note in attio by its id. it is implemented via delete https://api.attio.com/v2/notes/{note id} and handles note deletion by validating the provided note id. it complements attio create note functionality, providing complete note management capabilities within the attio platform. |
| `ATTIO_DELETE_RECORD` | Delete Record | This tool allows you to delete a record from attio permanently. the deletion is irreversible, and the data will eventually be removed from the system. |
| `ATTIO_FIND_RECORD` | Find Record | This tool allows users to find a record in attio by either its unique id or by searching using unique attributes. it provides two methods: one for directly retrieving a record by its id with the get /v2/objects/{object}/records/{record id} endpoint, and another for searching by attributes using the post /v2/objects/{object}/records/query endpoint. |
| `ATTIO_GET_OBJECT` | Get Object Details | This tool retrieves detailed information about a specific object type in attio, including all its attributes and their properties. this is useful for understanding what fields are available when creating or updating records of this type. |
| `ATTIO_LIST_LISTS` | List Lists | This tool retrieves all lists available in the attio workspace. the lists are returned sorted as they appear in the sidebar. this tool is essential for managing and navigating lists, and is a prerequisite for many list-related operations. it requires the list configuration:read permission scope. |
| `ATTIO_LIST_NOTES` | List Notes | This tool lists all notes associated with a specific record in attio. notes are returned in reverse chronological order (newest first). |
| `ATTIO_LIST_OBJECTS` | List Objects | This tool retrieves a list of all available objects (both system-defined and user-defined) in the attio workspace. it makes a get request to the /v2/objects endpoint and returns a json response containing key metadata about each object, which is fundamental for understanding and accessing the workspace's structure. |
| `ATTIO_LIST_RECORDS` | List Records | This tool lists records from a specific object type in attio. it provides simple pagination support and returns records in the order they were created. for complex filtering, use the findrecord action instead. standard object types include: people, companies, deals, users, workspaces. if you get a 404 error, verify the object type exists using the list objects action first. |
| `ATTIO_UPDATE_RECORD` | Update Record | This tool updates an existing record in attio for a specified object type (people, companies, deals, users, workspaces, etc.). it uses patch to partially update only the provided fields, leaving other fields unchanged. |

## Supported Triggers

None listed.

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

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

## How to build Attio MCP Agent with another framework

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

## Related Toolkits

- [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place.
- [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up.
- [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships.
- [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place.
- [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing.
- [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.
- [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities.
- [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place.
- [Bettercontact](https://composio.dev/toolkits/bettercontact) - Bettercontact is a smart contact enrichment tool for finding emails and phone numbers. It helps boost lead generation with automated, waterfall search across multiple sources.
- [Blackbaud](https://composio.dev/toolkits/blackbaud) - Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations.
- [Brilliant directories](https://composio.dev/toolkits/brilliant_directories) - Brilliant Directories is an all-in-one platform for building and managing online membership communities and business directories. It streamlines listings, member management, and engagement tools into a single, easy interface.
- [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently.
- [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools.
- [Dropcontact](https://composio.dev/toolkits/dropcontact) - Dropcontact is a B2B email finder and data enrichment service for professionals. It delivers verified email addresses and enriches contact info with up-to-date data.
- [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place.
- [Espocrm](https://composio.dev/toolkits/espocrm) - EspoCRM is an open-source web application for managing customer relationships. It helps businesses organize contacts, track leads, and streamline their sales process.
- [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools.
- [Firmao](https://composio.dev/toolkits/firmao) - Firmao is a business information platform offering company, industry, and market data. Use it to quickly research firms and gain competitive market insights.

## Frequently Asked Questions

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

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

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

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

---
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