How to integrate Diffbot MCP with Autogen

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Introduction

This guide walks you through connecting Diffbot to AutoGen using the Composio tool router. By the end, you'll have a working Diffbot agent that can extract specs and reviews from a product page, summarize key details from a news article url, list all bulk data extraction jobs for my account, get discussion threads from a forum post link through natural language commands.

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

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

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

The Diffbot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Diffbot account. It provides structured and secure access to web data extraction and analysis, so your agent can extract structured data from web pages, analyze content types, retrieve product details, manage bulk jobs, and search extracted datasets on your behalf.

  • Automatic content analysis and extraction: Let your agent analyze any web page and automatically extract structured data such as articles, products, events, images, or videos using AI-powered tools.
  • Article and discussion thread extraction: Effortlessly pull detailed metadata, authors, publication dates, and full discussion threads from news sites, blogs, forums, and comment sections.
  • Product and event data gathering: Instantly extract comprehensive product specifications, pricing, reviews, and event information including venues, dates, and descriptions from e-commerce or event pages.
  • Bulk job management and search: Enable your agent to list, monitor, and search across large-scale crawl or extraction jobs, making it easy to work with massive web data collections.
  • Account and usage insights: Retrieve your Diffbot account details, plan information, and usage statistics to stay on top of quotas and manage your web data operations efficiently.

Supported Tools & Triggers

Tools
Diffbot SearchTool to search data extracted by crawl or bulk jobs using dql queries.
Get Diffbot Account DetailsTool to retrieve account details, including plan information and usage statistics.
Diffbot AnalyzeTool to automatically determine a page's content type and route it to the appropriate extraction api.
Get Article DataTool to extract information from articles, including authors, publication dates, and images.
Get Discussion ThreadTool to extract threads of content from forums, comment sections, and review pages.
Diffbot Get EventTool to extract event details from web pages.
Diffbot Get ImageTool to extract detailed information about images, including dimensions and recognition data.
Diffbot Get ProductTool to extract product information such as specifications, prices, availability, and reviews.
Get Video DataTool to extract information from videos, including titles, descriptions, and embedded html.
List Bulk JobsTool to list all bulk jobs associated with a specific token.
Resolve Lost IDTool to resolve lost ids in the knowledge graph.
Start Bulk JobTool to start a bulk extract job.
Start Crawl JobTool to spider a site for links and process them with the extract api into a single collection.
Stop Bulk JobTool to stop a running bulk job.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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 Diffbot 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 Diffbot 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 Diffbot 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 Diffbot session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["diffbot"]
    )
    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 Diffbot 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 Diffbot assistant agent with MCP tools
    agent = AssistantAgent(
        name="diffbot_assistant",
        description="An AI assistant that helps with Diffbot 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 Diffbot 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 Diffbot 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 Diffbot 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 Diffbot and AutoGen:

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

How to build Diffbot MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Diffbot MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Diffbot MCP with Claude Agent SDK

Google ADK

Google ADK

Use Diffbot MCP with Google ADK

LangChain

LangChain

Use Diffbot MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Diffbot MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Diffbot MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Diffbot MCP with LlamaIndex

CrewAI

CrewAI

Use Diffbot MCP with CrewAI

FAQ

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

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

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

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

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