How to integrate Zenrows MCP with Claude Agent SDK

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Introduction

This guide walks you through connecting Zenrows to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Zenrows agent that can download a pdf of this news article, extract plain text from the given webpage, get latest property data from zillow, show my current zenrows api usage stats through natural language commands.

This guide will help you understand how to give your Claude Agent SDK agent real control over a Zenrows account through Composio's Zenrows 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 Claude/Anthropic and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Zenrows
  • Configure an AI agent that can use Zenrows as a tool
  • Run a live chat session where you can ask the agent to perform Zenrows operations

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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

The Zenrows MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zenrows account. It provides structured and secure access to advanced web scraping capabilities, so your agent can extract structured data, bypass CAPTCHAs, convert pages to PDF, and monitor your API usage on your behalf.

  • Intelligent web data extraction: Direct your agent to scrape and extract plain text or structured data from dynamic websites, including specialized real estate property data from platforms like Zillow or Idealista.
  • PDF and content generation: Ask your agent to convert any web page into a PDF or retrieve clean, formatted plain text for archiving, documentation, or offline reading.
  • Seamless CAPTCHA and block bypassing: Enable your agent to gather data from sites protected by CAPTCHAs or anti-bot systems without manual intervention.
  • Real-time API usage monitoring: Have the agent check your account’s current API usage, concurrency status, and limits to help manage credits and avoid interruptions.
  • Session and compression management: Instruct your agent to maintain consistent scraping sessions, handle compression to optimize bandwidth, and retrieve detailed response headers for debugging and performance optimization.

Supported Tools & Triggers

Tools
Get ZenRows API Usage StatisticsThis tool retrieves the current api usage statistics and limits for your zenrows account.
Get Concurrency StatusThis tool retrieves the current concurrency status of your zenrows api usage.
Get Detailed Concurrency StatusThis tool provides detailed information about the current concurrency status and limits of your zenrows account by making a request to the api and analyzing the response headers.
Get Original Status CodeThis tool retrieves the original http status code returned by the target website, which is useful for debugging purposes.
Get PDF from URLThis tool generates a pdf version of the scraped content from a given url.
Get Plaintext ResponseThis tool extracts plain text content from a webpage using the zenrows api.
Get Real Estate Property DataA specialized tool for extracting structured data from real estate platforms like zillow and idealista.
Get Response with CompressionA tool to fetch content from a url using the zenrows api with compression enabled to optimize bandwidth usage and improve performance.
Get response headersA tool to retrieve and parse response headers from zenrows api requests.
Get Session IDThis tool implements zenrows' session management functionality to maintain the same ip address across multiple requests for up to 10 minutes.
Get Walmart Product DetailsThis tool allows users to extract detailed product information from walmart using zenrows' specialized e-commerce scraping api.
Scrape urlScrape and extract data from a specified url.
Scrape url autoparseThe zenrows scrape url autoparse tool automatically parses and extracts structured data from any given url using intelligent parsing capabilities.
Scrape URL HTMLThis tool extracts raw html data from a given url using zenrows' universal scraper api.
Scrape URL with CSS SelectorsThis tool allows users to scrape specific elements from a webpage using css selectors.
Screenshot URLA tool to capture screenshots of web pages using zenrows api.

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

Before starting, make sure you have:
  • Composio API Key and Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Zenrows account
  • Some knowledge of Python

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • 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

pip install composio-anthropic claude-agent-sdk python-dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • composio-anthropic provides Composio integration for Anthropic
  • claude-agent-sdk is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude

Import dependencies

import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The load_dotenv() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Zenrows functionality

Create a Composio instance and Tool Router session

async def chat_with_remote_mcp():
    api_key = os.getenv("COMPOSIO_API_KEY")
    if not api_key:
        raise RuntimeError("COMPOSIO_API_KEY is not set")

    composio = Composio(api_key=api_key)

    # Create Tool Router session for Zenrows
    mcp_server = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zenrows"]
    )

    url = mcp_server.mcp.url

    if not url:
        raise ValueError("Session URL not found")
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Zenrows
  • The returned url is the MCP server URL that your agent will use

Configure Claude Agent with MCP

# Configure remote MCP server for Claude
options = ClaudeAgentOptions(
    permission_mode="bypassPermissions",
    mcp_servers={
        "composio": {
            "type": "http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    },
    system_prompt="You are a helpful assistant with access to Zenrows tools via Composio.",
    max_turns=10
)
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permission_mode="bypassPermissions" allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Zenrows
  • max_turns=10 limits the conversation length to prevent excessive API usage

Create client and start chat loop

# Create client with context manager
async with ClaudeSDKClient(options=options) as client:
    print("\nChat started. Type 'exit' or 'quit' to end.\n")

    # Main chat loop
    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit"}:
            print("Goodbye!")
            break

        # Send query
        await client.query(user_input)

        # Receive and print response
        print("Claude: ", end="", flush=True)
        async for message in client.receive_response():
            if hasattr(message, "content"):
                for block in message.content:
                    if hasattr(block, "text"):
                        print(block.text, end="", flush=True)
        print()
What's happening:
  • The Claude SDK client is created using the async context manager pattern
  • The agent processes each query and streams the response back in real-time
  • The chat loop continues until the user types 'exit' or 'quit'

Run the application

if __name__ == "__main__":
    asyncio.run(chat_with_remote_mcp())
What's happening:
  • This entry point runs the async chat_with_remote_mcp() function using asyncio.run()
  • The application will start, create the MCP connection, and begin the interactive chat session

Complete Code

Here's the complete code to get you started with Zenrows and Claude Agent SDK:

import asyncio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

async def chat_with_remote_mcp():
    api_key = os.getenv("COMPOSIO_API_KEY")
    if not api_key:
        raise RuntimeError("COMPOSIO_API_KEY is not set")

    composio = Composio(api_key=api_key)

    # Create Tool Router session for Zenrows
    mcp_server = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zenrows"]
    )

    url = mcp_server.mcp.url

    if not url:
        raise ValueError("Session URL not found")

    # Configure remote MCP server for Claude
    options = ClaudeAgentOptions(
        permission_mode="bypassPermissions",
        mcp_servers={
            "composio": {
                "type": "http",
                "url": url,
                "headers": {
                    "x-api-key": os.getenv("COMPOSIO_API_KEY")
                }
            }
        },
        system_prompt="You are a helpful assistant with access to Zenrows tools via Composio.",
        max_turns=10
    )

    # Create client with context manager
    async with ClaudeSDKClient(options=options) as client:
        print("\nChat started. Type 'exit' or 'quit' to end.\n")

        # Main chat loop
        while True:
            user_input = input("You: ").strip()
            if user_input.lower() in {"exit", "quit"}:
                print("Goodbye!")
                break

            # Send query
            await client.query(user_input)

            # Receive and print response
            print("Claude: ", end="", flush=True)
            async for message in client.receive_response():
                if hasattr(message, "content"):
                    for block in message.content:
                        if hasattr(block, "text"):
                            print(block.text, end="", flush=True)
            print()

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

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Zenrows through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Zenrows MCP Agent with another framework

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Mastra AI

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CrewAI

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FAQ

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

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

Can I use Tool Router MCP with Claude Agent SDK?

Yes, you can. Claude Agent SDK 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 Zenrows tools.

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

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

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