How to integrate Kadoa MCP with Autogen

This guide walks you through connecting Kadoa to AutoGen using the Composio tool router. By the end, you'll have a working Kadoa agent that can fetch the latest data from your workflow, check crawl status for session abc123, list all pages crawled in last run through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Kadoa account through Composio's Kadoa MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Kadoa is an API-first platform for building and managing workflows that extract data from unstructured sources. It helps automate and monitor extraction tasks at scale.

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Introduction

This guide walks you through connecting Kadoa to AutoGen using the Composio tool router. By the end, you'll have a working Kadoa agent that can fetch the latest data from your workflow, check crawl status for session abc123, list all pages crawled in last run through natural language commands.

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

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

Also integrate Kadoa with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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

The Kadoa MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kadoa account. It provides structured and secure access to your data extraction workflows, so your agent can launch crawls, monitor sessions, retrieve extracted data, and manage workflow configurations automatically on your behalf.

  • Automated workflow monitoring and management: Ask your agent to fetch workflow configurations, enable data validation, or get the latest results from any extraction workflow you have set up.
  • Crawling session control: Have your agent check the status of crawl sessions, list all crawled pages, and pull the raw content (HTML or Markdown) from any page processed by a workflow.
  • Notification channel setup and retrieval: Direct your agent to create notification channels, list available notification event types, and fetch specific channel configurations for streamlined alerting.
  • Location and environment awareness: Let your agent retrieve all supported locations to ensure workflows run in the right environment before launching new extraction jobs.
  • Seamless data access: Instruct your agent to quickly get the most recent data output from any workflow, keeping your automations and dashboards always up to date.

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

Supported Tools

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

Bulk Approve Validation Rules

Tool to bulk approve preview validation rules for a workflow.

Create Crawl Config

Tool to create a new crawling configuration in Kadoa.

Create Notification Channel

Tool to create a notification channel for alerts delivery.

Create Schema

Create a new data schema with specified fields and entity type.

Create Support Issue

Tool to create a support ticket in Kadoa.

Create Workflow Trigger

Tool to create a trigger that fires when a source workflow emits an event.

Delete All Validation Rules

Tool to soft-delete all validation rules for a specific workflow with optional audit trail.

Delete Crawl Configuration

Tool to delete a crawling configuration by its config ID.

Delete Notification Channel

Tool to delete a notification channel by its ID.

Delete Schema

Tool to delete a schema and all its revisions.

Delete Validation Rule

Tool to delete a validation rule from a Kadoa workflow.

Delete Validation Rules (Bulk)

Tool to bulk delete multiple validation rules for a workflow.

Delete Workflow

Delete a workflow permanently from your Kadoa account.

Delete Workflow Trigger

Tool to delete a trigger from a Kadoa workflow.

Disable Validation Rule

Tool to disable a validation rule with a mandatory reason.

Enable Data Validation

Tool to enable data validation on a specified workflow.

Execute Bulk Workflow Operations

Execute actions on multiple workflows at once.

Export Activity Events

Tool to export activity events from audit logs to CSV format for compliance and audit purposes.

Export Activity Workflows

Tool to export workflow configurations and metadata as CSV for portfolio reviews and compliance reporting.

Get Workflow by ID

Retrieve detailed configuration of a workflow by its ID.

Get all locations

Retrieves all available scraping proxy locations (countries) supported by Kadoa.

Get Crawl Bucket Data

Tool to retrieve file content from the Kadoa crawling bucket (HTML or screenshot).

Get Crawl Configuration

Tool to retrieve a crawling configuration by its ID.

Get Crawled Page Content

Tool to retrieve content of a crawled page.

Get Crawled Pages

Tool to list pages crawled during a session.

Get Crawl Status

Tool to fetch current status of a crawling session.

Get Event Type Details

Tool to retrieve details for a specific notification event type.

Get Notification Event Types

Tool to retrieve supported notification event types.

Get Latest Workflow Data

Retrieves the extracted data from a Kadoa workflow's most recent run (or a specific run if runId is provided).

Get Latest Workflow Validation

Retrieves the latest validation results for the most recent job of a workflow.

Get Notification Channel

Tool to retrieve details of a specific notification channel.

Get Notification Logs

Tool to retrieve notification event logs with optional filtering by workflow, event type, and date range.

Get Notification Setting

Retrieves a specific notification setting by its unique identifier.

Get Schema by ID

Retrieve a specific schema by its unique identifier.

Get Validation Anomalies

Tool to retrieve all anomalies for a specific validation.

Get Validation Anomalies By Rule

Tool to retrieve anomalies for a specific validation rule.

Get Validation Configuration

Tool to retrieve the data validation configuration for a specific workflow.

Get Validation Rule

Tool to retrieve a specific validation rule by its ID.

Get Workflow Audit Log

Retrieve audit log entries for a workflow.

Get Workflow Job

Tool to retrieve the current status and telemetry information for a specific workflow job.

Get Workflow Run History

Tool to fetch workflow run history.

Get Workflows

Retrieve a paginated list of workflows with optional filtering.

Get Workflow Trigger

Tool to retrieve a specific trigger for a workflow.

Get Workflow Validation Results

Retrieves the latest validation results for a specific workflow job.

Get Workspace Details

Tool to retrieve detailed information about a workspace (user, team, or organization).

List Activity Events

Tool to retrieve activity events from audit logs with basic filtering and pagination.

List Changes

Tool to retrieve all data changes detected across workflows in your Kadoa account.

List Crawl Sessions

Tool to retrieve a paginated list of crawling sessions with optional filtering.

List Job Validations

Tool to list all validation runs for a specific job with pagination support.

List Notification Channels

Tool to retrieve all notification channels configured for the account.

List Notification Settings

Tool to retrieve all notification settings, with optional filtering by workflow ID or event type.

List Schemas

Tool to retrieve all schemas accessible by the authenticated user.

List Support States

Tool to retrieve available support issue states.

List Validation Rules

Tool to list all data validation rules with optional pagination and filtering.

List Workflow Triggers

Tool to get all triggers where the specified workflow is the source.

Pause Crawl Session

Tool to pause an active crawling session.

Pause Workflow

Tool to pause a running or scheduled workflow.

Create Advanced Workflow

Tool to create an advanced workflow.

Start Crawl Session

Starts a new web crawling session to crawl and index pages from a website.

Create Notification Setting

Tool to create a notification setting linking channels to events.

Send Test Notification

Sends a test notification event to verify notification channel configurations are working correctly.

Subscribe to Webhook Events

Tool to subscribe to specified webhook events.

Create Workflow

Create a new Kadoa web scraping workflow.

Configure Workflow Monitoring

Configure monitoring and scheduling for a Kadoa workflow to detect data changes.

Generate Workflow Validation Rule

Generate an AI-powered data validation rule for a Kadoa workflow.

Update Notification Channel

Tool to update an existing notification channel.

Resume Crawl Session

Tool to resume a paused crawling session.

Resume Workflow

Resumes a paused, preview, or error workflow.

Run Ad-hoc Extraction

Tool to synchronously extract data from a URL using a given template.

Run Workflow

Tool to trigger a workflow to run immediately.

Schedule Validation Job

Tool to schedule a data validation job for a specific workflow job.

Unsubscribe from Webhook Events

Unsubscribe from webhook event notifications by deleting a notification setting.

Update Notification Settings

Tool to update existing notification settings for events.

Update Schema

Tool to update an existing Kadoa schema.

Update Validation Configuration

Tool to update the complete data validation configuration including alerting settings for a specific workflow.

Update Workflow Metadata

Tool to update workflow metadata such as name, description, tags, and configuration settings.

Update Workflow Trigger

Tool to update trigger properties including event type and enabled status.

FRAMEWORKS

How to build Kadoa MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Kadoa MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Kadoa MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Kadoa MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Kadoa MCP with Claude Cowork

Codex logo

Codex

Use Kadoa MCP with Codex

OpenClaw logo

OpenClaw

Use Kadoa MCP with OpenClaw

Hermes logo

Hermes

Use Kadoa MCP with Hermes

CLI logo

CLI

Use Kadoa MCP with CLI

Google ADK logo

Google ADK

Use Kadoa MCP with Google ADK

LangChain logo

LangChain

Use Kadoa MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Kadoa MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Kadoa MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Kadoa MCP with LlamaIndex

CrewAI logo

CrewAI

Use Kadoa MCP with CrewAI

FAQ

Frequently asked questions

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

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

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

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

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's immensely helped keep new users on the platform.

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Abhi Arya
Co-founder, Opennote

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

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CEO, Zams

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

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Founder, Extra Thursday

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

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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.

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