How to integrate Zenrows MCP with Google ADK

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Introduction

This guide walks you through connecting Zenrows to Google ADK 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 Google ADK 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 a Zenrows account set up and connected to Composio
  • Install the Google ADK and Composio packages
  • Create a Composio Tool Router session for Zenrows
  • Build an agent that connects to Zenrows through MCP
  • Interact with Zenrows using natural language

What is Google ADK?

Google ADK (Agents Development Kit) is Google's framework for building AI agents powered by Gemini models. It provides tools for creating agents that can use external services through the Model Context Protocol.

Key features include:

  • Gemini Integration: Native support for Google's Gemini models
  • MCP Toolset: Built-in support for Model Context Protocol tools
  • Streamable HTTP: Connect to external services through streamable HTTP
  • CLI and Web UI: Run agents via command line or web interface

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:
  • A Google API key for Gemini models
  • A Composio account and API key
  • Python 3.9 or later installed
  • Basic familiarity with Python

Getting API Keys for Google and Composio

Google API Key
  • Go to Google AI Studio and create an API key.
  • Copy the key and keep it safe. You will put this in GOOGLE_API_KEY.
Composio API Key and User ID
  • Log in to the Composio dashboard.
  • Go to Settings → API Keys and copy your Composio API key. Use this for COMPOSIO_API_KEY.
  • Decide on a stable user identifier to scope sessions, often your email or a user ID. Use this for COMPOSIO_USER_ID.

Install dependencies

bash
pip install google-adk composio-google python-dotenv

Inside your virtual environment, install the required packages.

What's happening:

  • google-adk is Google's Agents Development Kit
  • composio connects your agent to Zenrows via MCP
  • composio-google provides the Google ADK provider
  • python-dotenv loads environment variables

Set up ADK project

bash
adk create my_agent

Set up a new Google ADK project.

What's happening:

  • This creates an agent folder with a root agent file and .env file

Set environment variables

bash
GOOGLE_API_KEY=your-google-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id-or-email

Save all your credentials in the .env file.

What's happening:

  • GOOGLE_API_KEY authenticates with Google's Gemini models
  • COMPOSIO_API_KEY authenticates with Composio
  • COMPOSIO_USER_ID identifies the user for session management

Import modules and validate environment

python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()

warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")
What's happening:
  • os reads environment variables
  • Composio is the main Composio SDK client
  • GoogleProvider declares that you are using Google ADK as the agent runtime
  • Agent is the Google ADK LLM agent class
  • McpToolset lets the ADK agent call MCP tools over HTTP

Create Composio client and Tool Router session

python
print("Initializing Composio client...")
composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

print("Creating Composio session...")
composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["zenrows"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url
print(f"Composio MCP HTTP URL: {COMPOSIO_MCP_URL}")
What's happening:
  • Authenticates to Composio with your API key
  • Declares Google ADK as the provider
  • Spins up a short-lived MCP endpoint for your user and selected toolkit
  • Stores the MCP HTTP URL for the ADK MCP integration

Set up the McpToolset and create the Agent

python
print("Creating Composio toolset for the agent...")
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )
)

root_agent = Agent(
    model="gemini-2.5-pro",
    name="composio_agent",
    description="An agent that uses Zenrows tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Zenrows operations."
    ),
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
What's happening:
  • Connects the ADK agent to the Composio MCP endpoint through McpToolset
  • Uses Gemini as the model powering the agent
  • Lists exact tool names in instruction to reduce misnamed tool calls

Run the agent

bash
# Run in CLI mode
adk run my_agent

# Or run in web UI mode
adk web
Execute the agent from the project root. The web command opens a web portal where you can chat with the agent. What's happening:
  • adk run runs the agent in CLI mode
  • adk web opens a web UI for interactive testing

Complete Code

Here's the complete code to get you started with Zenrows and Google ADK:

python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

def main():
    try:
        load_dotenv()

        warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

        GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
        COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
        COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

        if not GOOGLE_API_KEY:
            raise ValueError("GOOGLE_API_KEY is not set in the environment.")
        if not COMPOSIO_API_KEY:
            raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
        if not COMPOSIO_USER_ID:
            raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

        print("Initializing Composio client...")
        composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

        print("Creating Composio session...")
        composio_session = composio_client.create(
            user_id=COMPOSIO_USER_ID,
            toolkits=["zenrows"],
        )

        COMPOSIO_MCP_URL = composio_session.mcp.url
        print(f"Composio MCP HTTP URL: {COMPOSIO_MCP_URL}")

        print("Creating Composio toolset for the agent...")
        composio_toolset = McpToolset(
            connection_params=StreamableHTTPConnectionParams(
                url=COMPOSIO_MCP_URL,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
            )
        )

        root_agent = Agent(
            model="gemini-2.5-pro",
            name="composio_agent",
            description="An agent that uses Zenrows tools to perform actions.",
            instruction=(
                "You are a helpful assistant connected to Composio. "
                "You have the following tools available: "
                "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
                "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
                "Use these tools to help users with Zenrows operations."
            ),
            tools=[composio_toolset],
        )

        print("\nAgent setup complete. You can now run this agent directly ;)")

    except Exception as e:
        print(f"\nAn error occurred during agent setup: {e}")

if __name__ == "__main__":
    main()

Conclusion

You've successfully integrated Zenrows with the Google ADK through Composio's MCP Tool Router. Your agent can now interact with Zenrows using natural language commands.

Key takeaways:

  • The Tool Router approach dynamically routes requests to the appropriate Zenrows tools
  • Environment variables keep your credentials secure and separate from code
  • Clear agent instructions reduce tool calling errors
  • The ADK web UI provides an interactive interface for testing and development

You can extend this setup by adding more toolkits to the toolkits array in your session configuration.

How to build Zenrows MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Zenrows MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Zenrows MCP with Claude Agent SDK

LangChain

LangChain

Use Zenrows MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Zenrows MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Zenrows MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Zenrows MCP with LlamaIndex

CrewAI

CrewAI

Use Zenrows MCP with CrewAI

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 Google ADK?

Yes, you can. Google ADK 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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