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How to integrate Scrapingbee MCP with Pydantic AI

Connect Pydantic AI to Scrapingbee MCP. Extract product prices from amazon search results, fetch latest news headlines from bbc homepage, and more using natural language, with authentication handled for you.

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Scrapingbee is a web scraping API that handles browsers and proxy rotation for you. It lets you extract HTML from any website with a single API call.

5 Tools

Introduction

This guide walks you through connecting Scrapingbee to Pydantic AI using the Composio tool router. By the end, you'll have a working Scrapingbee agent that can fetch page HTML, extract structured data, scrape through stealth proxies, and check your usage stats through natural language commands.

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

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

Also integrate Scrapingbee with

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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Scrapingbee
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Scrapingbee workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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

The Scrapingbee MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Scrapingbee account. It provides structured and secure access to powerful web scraping tools, so your agent can extract data, fetch HTML, bypass anti-bot measures, and monitor your usage—all without manual code.

  • Structured data extraction from any webpage: Let your agent pull tables, lists, or custom data using CSS or XPath selectors with ScrapingBee's extraction rules.
  • Fetch full HTML or page screenshots: Ask your agent to retrieve raw page markup or rendered screenshots, including support for JavaScript-heavy sites.
  • Proxy and stealth scraping: Enable your agent to scrape sites that block bots by routing requests through ScrapingBee proxies or stealth modes to bypass anti-bot defenses.
  • Resource control and custom rendering: Have your agent fine-tune scraping with options to block resources, control JS rendering, and speed up extraction for tricky websites.
  • Monitor account usage and limits: Keep track of your remaining ScrapingBee credits and usage statistics directly through your agent for seamless quota management.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Scrapingbee
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Scrapingbee
  • MCPServerStreamableHTTP connects to the Scrapingbee MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Scrapingbee
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["scrapingbee"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Scrapingbee tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
scrapingbee_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[scrapingbee_mcp],
    instructions=(
        "You are a Scrapingbee assistant. Use Scrapingbee tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Scrapingbee endpoint
  • The agent uses GPT-5 to interpret user commands and perform Scrapingbee operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Scrapingbee.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Scrapingbee API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Scrapingbee and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Scrapingbee
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["scrapingbee"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    scrapingbee_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[scrapingbee_mcp],
        instructions=(
            "You are a Scrapingbee assistant. Use Scrapingbee tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Scrapingbee.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Scrapingbee through Composio's Tool Router. With this setup, your agent can perform real Scrapingbee actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Scrapingbee for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

ScrapingBee Data Extraction

Extract structured data from a webpage using CSS or XPath selectors via ScrapingBee's extract_rules feature.

ScrapingBee HTML Fetch

Fetch page content or a screenshot through ScrapingBee's HTML API, with optional JavaScript rendering, proxy and resource controls.

ScrapingBee Proxy Mode

Fetch web content through ScrapingBee's HTML API with optional JavaScript rendering, proxy selection, and resource blocking.

ScrapingBee Stealth Proxy

Fetch web content through ScrapingBee with optional stealth proxy and JavaScript rendering for sites with anti-bot measures.

ScrapingBee Usage Stats

Retrieve ScrapingBee account usage statistics, including credit usage, concurrency limits and current concurrency, and subscription renewal date.

FRAMEWORKS

How to build Scrapingbee MCP Agent with another framework

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OpenAI Agents SDK logo

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Claude Agent SDK logo

Claude Agent SDK

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Codex logo

Codex

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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Atomic Agent logo

Atomic Agent

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Google ADK logo

Google ADK

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LangChain logo

LangChain

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Vercel AI SDK logo

Vercel AI SDK

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Mastra AI logo

Mastra AI

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LlamaIndex logo

LlamaIndex

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CrewAI logo

CrewAI

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AutoGen logo

AutoGen

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FAQ

Frequently asked questions

With a standalone Scrapingbee MCP server, the agents and LLMs can only access a fixed set of Scrapingbee tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Scrapingbee and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pydantic AI 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 Scrapingbee tools.

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

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