Agenty with AutoGen

How to integrate Agenty MCP with Autogen

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Introduction Also integrate Agenty with TL;DR What is AutoGen What is the Agenty MCP server Supported Tools & Triggers Creating MCP Server - Stand-alone vs Composio SDK Step-by-step Guide Complete Code Conclusion How to build Agenty MCP Agent with another framework Explore Other Toolkits FAQ

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Introduction

This guide walks you through connecting Agenty to AutoGen using the Composio tool router. By the end, you'll have a working Agenty agent that can clone your top-performing agent for news sites, list all your running web scraping agents, create a new agent to monitor product prices through natural language commands.

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

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

Also integrate Agenty with

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

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

The Agenty MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Agenty account. It provides structured and secure access to your web scraping agents and automation tools, so your agent can perform actions like creating, managing, cloning, and monitoring scraping agents, as well as handling API keys and templates—all on your behalf.

Agent creation and configuration: Instantly create new scraping or automation agents, set up their configurations, and optionally auto-start them—all without manual coding.
Clone and update agents: Duplicate existing agents to streamline workflows or update agent settings to refine your data extraction processes.
Fetch and manage agents: List all active agents in your account, retrieve details for any agent, and organize your entire automation fleet from a single place.
Template selection and management: Browse public agent templates or sample agents, making it easy to kickstart new projects or standardize scraping tasks.
API key management: Create, download, or delete API keys for secure programmatic access and efficient credential management, keeping your automation environment safe and organized.

Supported Tools & Triggers

Tools

Add List RowsTool to add new rows to a list.

Create AgentCreates a new Agenty agent for web scraping, change detection, crawling, map monitoring, or brand monitoring.

Get Agent TemplatesTool to fetch all public agent templates and sample agents.

Delete Agent by IDTool to delete a single agent by its ID.

Fetch all agentsTool to fetch all active agents under an account.

Get Agent by IDRetrieves complete details of a specific agent including its configuration, input settings, scheduler, and metadata.

Update Agent by IDUpdates an existing agent's configuration, settings, and metadata.

Create API KeyCreates a new API key for programmatic access to the Agenty API.

Delete API key by IDDelete an API key by its unique identifier.

Download API keysTool to download all API keys under an account in CSV format.

Get all API keysTool to retrieve all API keys under an account.

Get API key by IDRetrieves detailed information about a specific API key by its ID.

Reset API key by IDResets (regenerates) the secret value of an existing API key.

Update API key by IDUpdates an existing API key's name and role by its unique identifier.

Capture ScreenshotTool to capture a full-page or visible screenshot of any webpage URL.

Capture Screenshot with OptionsTool to capture webpage screenshots with extensive customization options including full-page capture, image format, quality settings, viewport configuration, and post-processing.

Change API key status by IDToggles the enabled/disabled status of an API key.

Get all connectionsRetrieves all connections from your Agenty account.

Convert URL to PDFTool to convert a webpage URL to a PDF document.

Convert URL to PDF with OptionsTool to convert a URL or raw HTML to PDF with customizable options.

Copy AgentTool to copy an existing agent by its ID, creating a duplicate with optionally a new name.

Create WorkflowCreates a new workflow in Agenty to automate actions based on agent events.

Get dashboard reports and usageTool to fetch account reports like pages used by agent, date, and product.

Delete List Row by IDTool to delete a specific row from a list by its unique identifier.

Delete List Rows by IDsTool to delete specific rows from a list by their IDs.

Delete ProjectTool to delete a project by its ID.

Delete ScheduleTool to delete a schedule for an agent by its agent ID.

Delete Workflow by IDTool to delete a workflow by its ID.

Download Agent ResultTool to download agent results by agent ID in CSV, TSV or JSON format.

Download List RowsTool to download list rows as CSV file.

Download usersTool to download users list in CSV format.

Download workflowsTool to download all workflows in CSV format.

Extract Structured DataTool to auto-extract structured data from a webpage including schema.

Extract Structured Data from URLTool to auto-extract structured data from a webpage URL.

Get Agent ResultTool to get the most recent result data for an agent.

Get all team membersTool to retrieve all team members (users) under an account.

Get URL RedirectsTool to get the complete redirect chain for a URL.

Get Job ResultTool to get the result data from a completed job.

Get list by IDRetrieves detailed information about a specific list by its ID.

Get List Row by IDTool to fetch a specific row by its ID from a list.

Get Page ContentTool to fetch the complete HTML content of any webpage URL.

Get Page Content with OptionsTool to fetch HTML content of a webpage with custom options including ad blocking.

Get Project by IDRetrieves complete details of a specific project by its ID, including name, description, creator information, and timestamps.

Get Redirects with OptionsTool to get the complete redirect chain of a URL with custom navigation options.

Get Agent ScheduleTool to retrieve the schedule configuration for a specific agent.

Get User by IDTool to retrieve detailed information about a user by their ID.

Get Workflow by IDRetrieves complete details of a specific workflow by its ID.

Get agent input by IDRetrieves the input configuration for a specific agent by its ID.

Update Input by Agent IDUpdates the input configuration for a specific agent in Agenty.

Download jobsTool to download all jobs in CSV format.

Download job file by IDTool to download output files by job ID.

Download Job Result by IDTool to download the agent output result by job ID.

Fetch all jobsTool to fetch all jobs under an account.

Get Job by IDRetrieves comprehensive details about a specific job including its status, progress metrics (pages processed/succeeded/failed), timing information (created/started/completed times), resource consumption (page credits), and any error messages.

Get Job Logs by IDTool to fetch logs for a given job by its ID.

List job output filesLists all output files generated by a specific job.

Start Agent JobTool to start a new agent job.

Stop Job by IDTool to stop a running job by job ID.

Clear List RowsTool to clear all rows in a list by its ID.

Create ListTool to create a new list.

Delete List by IDTool to delete a specific list by its ID.

Download listsTool to download all lists in CSV format.

Get all listsTool to retrieve all lists under an account.

Fetch List Rows by IDTool to fetch all rows in a specified list.

Update List by IDTool to update a list's name and optionally description by list ID.

Upload CSV file to ListTool to upload a CSV file to an Agenty list for bulk import of data rows.

Patch WorkflowTool to partially update a workflow by ID.

Add Agents to ProjectAdd one or more agents to an Agenty project to organize and group related agents together.

Create ProjectCreates a new project in Agenty.

Get all projectsRetrieve all projects in the authenticated user's account.

Remove Agent from ProjectRemove an agent from an Agenty project.

Scrape Webpage DataTool to scrape data from any webpage using jQuery/CSS selectors.

Toggle Agent ScheduleTool to toggle schedule on/off for an agent.

Transfer Agent OwnershipTool to transfer agent ownership to another Agenty account.

Update List RowTool to update a specific row in a list by list ID and row ID.

Update ProjectUpdate an existing project's name and description in Agenty.

Update Agent ScheduleUpdates the schedule configuration for a specific agent.

Update User by IDTool to update a user's information by user ID.

Update WorkflowTool to update an existing workflow's configuration by workflow ID.

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:

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

Step-by-step Guide

Prerequisites

You will need:

A Composio API key
An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
A Agenty account you can connect to Composio
Some basic familiarity with Autogen and Python async

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.

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 Agenty via MCP
autogen-agentchat provides the AssistantAgent class
autogen-ext-openai provides the OpenAI model client
autogen-ext-tools provides MCP workbench support

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 Agenty connections to use

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 Agenty session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["agenty"]
    )
    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 Agenty tools
session.mcp.url is the MCP endpoint that Autogen will connect to

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

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 Agenty assistant agent with MCP tools
    agent = AssistantAgent(
        name="agenty_assistant",
        description="An AI assistant that helps with Agenty 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 Agenty tools from the workbench

Run the interactive chat loop

python

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Agenty 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 Agenty 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 Agenty 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 Agenty session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["agenty"]
    )
    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 Agenty assistant agent with MCP tools
        agent = AssistantAgent(
            name="agenty_assistant",
            description="An AI assistant that helps with Agenty 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 Agenty 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 Agenty 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 Agenty, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Agenty MCP Agent with another framework

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OpenClaw

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Hermes

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CLI

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Google ADK

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LangChain

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Vercel AI SDK

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Mastra AI

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TOOLKIT MARKETPLACE

FAQ

What are the differences in Tool Router MCP and Agenty MCP?

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

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

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

Used by agents from

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Harsha GaddipatiCo-founder, Slashy

Karan skipped his own birthday party to fix our critical issue. It was 10 pm and he diverted his Waymo to help us instead. This really sets the bar, shows you the commitment you need to have when users rely on your software.

Abhi AryaCo-founder, Opennote

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it has immensely helped in keeping new users on the platform.

Nirman DaveCEO, Zams

We chose Composio over Pipedream because it delivered depth where it mattered. It supported niche tools and tricky edge cases that other platforms simply ignored. Giving us confidence to scale without compromising.

Ryan YuFounder, Extra Thursday

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down in the complexities of managing agent auth would have been a death sentence for Extra Thursday.

Tomisin JenrolaFounder & CEO, SwarmZero

Before partnering with Composio, adding tool integrations was a slow, resource-intensive process. Each integration could take weeks or months of engineering time, and maintaining them meant constantly keeping up with API changes.

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

How to integrate Agenty MCP with Autogen

Table of Contents

Connect Agenty without Auth hassles

Introduction

Also integrate Agenty with

TL;DR

What is AutoGen?

What is the Agenty MCP server, and what's possible with it?

Supported Tools & Triggers

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies and create Tool Router session

Configure MCP parameters for Autogen

Create the model client and agent

Run the interactive chat loop

Complete Code

Conclusion

How to build Agenty MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Excel

21risk

Abstract

FAQ

What are the differences in Tool Router MCP and Agenty MCP?

Can I use Tool Router MCP with Autogen?

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

How safe is my data with Composio Tool Router?

Used by agents from

Never worry about agent reliability