How to integrate Kadoa MCP with Autogen

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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

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.

Supported Tools & Triggers

Tools
Bulk Approve Validation RulesTool to bulk approve preview validation rules for a workflow.
Create Crawl ConfigTool to create a new crawling configuration in Kadoa.
Create Notification ChannelTool to create a notification channel for alerts delivery.
Create SchemaCreate a new data schema with specified fields and entity type.
Create Support IssueTool to create a support ticket in Kadoa.
Create Workflow TriggerTool to create a trigger that fires when a source workflow emits an event.
Delete All Validation RulesTool to soft-delete all validation rules for a specific workflow with optional audit trail.
Delete Crawl ConfigurationTool to delete a crawling configuration by its config ID.
Delete Notification ChannelTool to delete a notification channel by its ID.
Delete SchemaTool to delete a schema and all its revisions.
Delete Validation RuleTool to delete a validation rule from a Kadoa workflow.
Delete Validation Rules (Bulk)Tool to bulk delete multiple validation rules for a workflow.
Delete WorkflowDelete a workflow permanently from your Kadoa account.
Delete Workflow TriggerTool to delete a trigger from a Kadoa workflow.
Disable Validation RuleTool to disable a validation rule with a mandatory reason.
Enable Data ValidationTool to enable data validation on a specified workflow.
Execute Bulk Workflow OperationsExecute actions on multiple workflows at once.
Export Activity EventsTool to export activity events from audit logs to CSV format for compliance and audit purposes.
Export Activity WorkflowsTool to export workflow configurations and metadata as CSV for portfolio reviews and compliance reporting.
Get Workflow by IDRetrieve detailed configuration of a workflow by its ID.
Get all locationsRetrieves all available scraping proxy locations (countries) supported by Kadoa.
Get Crawl Bucket DataTool to retrieve file content from the Kadoa crawling bucket (HTML or screenshot).
Get Crawl ConfigurationTool to retrieve a crawling configuration by its ID.
Get Crawled Page ContentTool to retrieve content of a crawled page.
Get Crawled PagesTool to list pages crawled during a session.
Get Crawl StatusTool to fetch current status of a crawling session.
Get Event Type DetailsTool to retrieve details for a specific notification event type.
Get Notification Event TypesTool to retrieve supported notification event types.
Get Latest Workflow DataRetrieves the extracted data from a Kadoa workflow's most recent run (or a specific run if runId is provided).
Get Latest Workflow ValidationRetrieves the latest validation results for the most recent job of a workflow.
Get Notification ChannelTool to retrieve details of a specific notification channel.
Get Notification LogsTool to retrieve notification event logs with optional filtering by workflow, event type, and date range.
Get Notification SettingRetrieves a specific notification setting by its unique identifier.
Get Schema by IDRetrieve a specific schema by its unique identifier.
Get Validation AnomaliesTool to retrieve all anomalies for a specific validation.
Get Validation Anomalies By RuleTool to retrieve anomalies for a specific validation rule.
Get Validation ConfigurationTool to retrieve the data validation configuration for a specific workflow.
Get Validation RuleTool to retrieve a specific validation rule by its ID.
Get Workflow Audit LogRetrieve audit log entries for a workflow.
Get Workflow JobTool to retrieve the current status and telemetry information for a specific workflow job.
Get Workflow Run HistoryTool to fetch workflow run history.
Get WorkflowsRetrieve a paginated list of workflows with optional filtering.
Get Workflow TriggerTool to retrieve a specific trigger for a workflow.
Get Workflow Validation ResultsRetrieves the latest validation results for a specific workflow job.
Get Workspace DetailsTool to retrieve detailed information about a workspace (user, team, or organization).
List Activity EventsTool to retrieve activity events from audit logs with basic filtering and pagination.
List ChangesTool to retrieve all data changes detected across workflows in your Kadoa account.
List Crawl SessionsTool to retrieve a paginated list of crawling sessions with optional filtering.
List Job ValidationsTool to list all validation runs for a specific job with pagination support.
List Notification ChannelsTool to retrieve all notification channels configured for the account.
List Notification SettingsTool to retrieve all notification settings, with optional filtering by workflow ID or event type.
List SchemasTool to retrieve all schemas accessible by the authenticated user.
List Support StatesTool to retrieve available support issue states.
List Validation RulesTool to list all data validation rules with optional pagination and filtering.
List Workflow TriggersTool to get all triggers where the specified workflow is the source.
Pause Crawl SessionTool to pause an active crawling session.
Pause WorkflowTool to pause a running or scheduled workflow.
Create Advanced WorkflowTool to create an advanced workflow.
Start Crawl SessionStarts a new web crawling session to crawl and index pages from a website.
Create Notification SettingTool to create a notification setting linking channels to events.
Send Test NotificationSends a test notification event to verify notification channel configurations are working correctly.
Subscribe to Webhook EventsTool to subscribe to specified webhook events.
Create WorkflowCreate a new Kadoa web scraping workflow.
Configure Workflow MonitoringConfigure monitoring and scheduling for a Kadoa workflow to detect data changes.
Generate Workflow Validation RuleGenerate an AI-powered data validation rule for a Kadoa workflow.
Update Notification ChannelTool to update an existing notification channel.
Resume Crawl SessionTool to resume a paused crawling session.
Resume WorkflowResumes a paused, preview, or error workflow.
Run Ad-hoc ExtractionTool to synchronously extract data from a URL using a given template.
Run WorkflowTool to trigger a workflow to run immediately.
Schedule Validation JobTool to schedule a data validation job for a specific workflow job.
Unsubscribe from Webhook EventsUnsubscribe from webhook event notifications by deleting a notification setting.
Update Notification SettingsTool to update existing notification settings for events.
Update SchemaTool to update an existing Kadoa schema.
Update Validation ConfigurationTool to update the complete data validation configuration including alerting settings for a specific workflow.
Update Workflow MetadataTool to update workflow metadata such as name, description, tags, and configuration settings.
Update Workflow TriggerTool to update trigger properties including event type and enabled status.

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

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

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 Kadoa 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 Kadoa 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 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

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 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

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.

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FAQ

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

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.

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 Kadoa tools.

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

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.

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 Kadoa data and credentials are handled as safely as possible.

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