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How to integrate Webscraping ai MCP with Pydantic AI

Connect Pydantic AI to Webscraping ai MCP. Extract product prices from amazon listings, get latest headlines from bbc homepage, and more using natural language, with authentication handled for you.

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Api Key

Webscraping ai is a powerful API for extracting website data with JS rendering and proxy rotation. It lets you reliably scrape and parse dynamic web content at scale.

7 Tools

Introduction

This guide walks you through connecting Webscraping ai to Pydantic AI using the Composio tool router. By the end, you'll have a working Webscraping ai agent that can fetch rendered HTML and text, extract fields with AI, ask questions about web pages, and check your quota through natural language commands.

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

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

Also integrate Webscraping ai 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 Webscraping ai
  • 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 Webscraping ai 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 Webscraping ai MCP server, and what's possible with it?

The Webscraping ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Webscraping ai account. It provides structured and secure access to web scraping capabilities, so your agent can retrieve raw HTML, extract rendered web content, parse text, and monitor your API usage on your behalf.

  • Retrieve raw HTML from any webpage: Let your agent fetch the unprocessed HTML content of any website for analysis or processing.
  • Extract fully rendered HTML with JavaScript support: Have your agent capture the final, JavaScript-rendered HTML—great for sites that rely on dynamic content.
  • Get plain text from web pages: Direct your agent to extract just the readable text from any URL, skipping all the markup and scripts.
  • Monitor API usage and quota: Your agent can check your account's API call limits and current usage, so you always know where you stand.

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 Webscraping ai
  • 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 Webscraping ai
  • MCPServerStreamableHTTP connects to the Webscraping ai 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 Webscraping ai
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["webscraping_ai"],
    )
    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 Webscraping ai 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
webscraping_ai_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[webscraping_ai_mcp],
    instructions=(
        "You are a Webscraping ai assistant. Use Webscraping ai tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Webscraping ai endpoint
  • The agent uses GPT-5 to interpret user commands and perform Webscraping ai 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 Webscraping ai.\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
  • Webscraping ai 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 Webscraping ai 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 Webscraping ai
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["webscraping_ai"],
    )
    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
    webscraping_ai_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[webscraping_ai_mcp],
        instructions=(
            "You are a Webscraping ai assistant. Use Webscraping ai 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 Webscraping ai.\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 Webscraping ai through Composio's Tool Router. With this setup, your agent can perform real Webscraping ai 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 + Webscraping ai 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 Webscraping ai action and event your agent gets out of the box.

Get account usage and quota

Tool to retrieve account API call quota and usage.

Ask Question About Web Page

Get an LLM answer to a question about a web page for AI-powered analysis or extraction.

Extract Fields with AI

Tool to extract structured data fields from a web page using AI.

Get Rendered HTML

Tool to retrieve fully rendered HTML of a webpage.

Get Selected HTML

Tool to extract HTML from specific page elements using CSS selectors.

Get Selected Multiple Elements

Extract HTML from multiple areas of a web page using its URL and CSS selectors, without parsing the page yourself.

Get Text

Retrieve text content from a specified web page.

FRAMEWORKS

How to build Webscraping ai MCP Agent with another framework

Claude Code logo

Claude Code

Use Webscraping ai MCP with Claude Code

Claude Cowork logo

Claude Cowork

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OpenAI Agents SDK logo

OpenAI Agents SDK

Use Webscraping ai MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Webscraping ai MCP with Claude Agent SDK

Codex logo

Codex

Use Webscraping ai MCP with Codex

OpenClaw logo

OpenClaw

Use Webscraping ai MCP with OpenClaw

Hermes logo

Hermes

Use Webscraping ai MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Webscraping ai MCP with Atomic Agent

Google ADK logo

Google ADK

Use Webscraping ai MCP with Google ADK

LangChain logo

LangChain

Use Webscraping ai MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Webscraping ai MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Webscraping ai MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Webscraping ai MCP with LlamaIndex

CrewAI logo

CrewAI

Use Webscraping ai MCP with CrewAI

AutoGen logo

AutoGen

Use Webscraping ai MCP with AutoGen

FAQ

Frequently asked questions

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

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

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