# How to integrate Scrape do MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Scrape do MCP with OpenAI Agents SDK",
  "toolkit": "Scrape do",
  "toolkit_slug": "scrape_do",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/scrape_do/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/scrape_do/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:24:44.960Z"
}
```

## Introduction

This guide walks you through connecting Scrape do to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Scrape do agent that can scrape product prices from a dynamic website, extract news headlines with javascript rendering, bypass cloudflare to get full page html through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Scrape do account through Composio's Scrape do MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Scrape do with

- [Claude Agent SDK](https://composio.dev/toolkits/scrape_do/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/scrape_do/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/scrape_do/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/scrape_do/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/scrape_do/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/scrape_do/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/scrape_do/framework/cli)
- [Google ADK](https://composio.dev/toolkits/scrape_do/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/scrape_do/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/scrape_do/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/scrape_do/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/scrape_do/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/scrape_do/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Scrape do
- Configure an AI agent that can use Scrape do as a tool
- Run a live chat session where you can ask the agent to perform Scrape do operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## What is the Scrape do MCP server, and what's possible with it?

The Scrape do MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Scrape do account. It provides structured and secure access to robust web scraping tools, so your agent can perform actions like scraping dynamic pages, managing sessions, setting custom headers or proxies, and extracting structured data from any website on your behalf.
- Dynamic page scraping with headless browsers: Retrieve fully rendered HTML content from JavaScript-heavy or protected websites by leveraging advanced browser emulation and proxy rotation.
- Custom scraping session management: Set device type, cookies, wait times, and custom headers to imitate different users, maintain sessions, or access device-specific content for tailored data extraction.
- Proxy and anti-bot bypass control: Enable super or proxy modes to utilize residential, mobile, or datacenter proxies, helping your agent bypass strict anti-bot systems and geo-restrictions seamlessly.
- Targeted resource filtering: Block specific URLs like ads or analytics scripts during scraping to increase speed, avoid distractions, and improve privacy.
- Account usage and statistics retrieval: Access real-time usage stats, subscription status, and remaining request limits so your agent can monitor scraping quotas and avoid interruptions.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SCRAPE_DO_CANCEL_ASYNC_JOB` | Cancel Async Job | Tool to cancel an asynchronous scraping job. Use when you need to stop processing of pending tasks in a job. Completed tasks remain available. |
| `SCRAPE_DO_CREATE_ASYNC_JOB` | Create Async Scraping Job | Tool to create an asynchronous scraping job with specified targets and options. Use when you need to scrape multiple URLs in parallel without waiting for results. Returns a job ID immediately for polling results later via the get job status action. |
| `SCRAPE_DO_GET_ACCOUNT_INFO` | Get Account Information | Retrieves account information and usage statistics from Scrape.do. This action makes a GET request to the Scrape.do info endpoint to fetch: - Subscription status - Concurrent request limits and usage - Monthly request limits and remaining requests - Real-time usage statistics Rate limit: Maximum 10 requests per minute. Use remaining request counts to monitor credits proactively, as different scraping operations (e.g., rendered-page requests) consume varying credit amounts and exhaustion mid-run causes failures. |
| `SCRAPE_DO_GET_AMAZON_OFFERS` | Get Amazon Product Offers | Get all seller offers for any Amazon product. Retrieves every seller listing including pricing, shipping costs, seller information, and Buy Box status in structured JSON format. Use when you need to compare prices across multiple sellers or find the best deal for a specific product. |
| `SCRAPE_DO_GET_AMAZON_PRODUCT` | Get Amazon product details | Extract structured product data from Amazon product detail pages (PDP). Returns comprehensive product information including title, pricing, ratings, images, best seller rankings, and technical specifications in JSON format. |
| `SCRAPE_DO_GET_AMAZON_RAW_HTML` | Get Amazon raw HTML | Tool to get raw HTML from any Amazon page with ZIP code geo-targeting. Use when you need complete unprocessed HTML source from Amazon URLs with location-based targeting. Ideal for scraping pages not covered by other structured endpoints. |
| `SCRAPE_DO_GET_ASYNC_ACCOUNT_INFO` | Get Async API Account Information | Tool to get account information for the Async API including concurrency limits and usage statistics. Use when you need to check available concurrency slots, active jobs, or remaining credits for Async API operations. |
| `SCRAPE_DO_GET_ASYNC_JOB` | Get Async Job Details | Tool to retrieve details and status of a specific asynchronous scraping job. Use when you need to check the progress, status, or results of a previously created async job. Returns job metadata including creation time, completion time, task counts, and detailed task list. |
| `SCRAPE_DO_GET_ASYNC_TASK` | Get Async Task Result | Tool to retrieve the result of a specific task within an asynchronous job. Returns the scraped content for that particular URL. Use when you need to check the status and result of a previously submitted async scraping task. |
| `SCRAPE_DO_SCRAPE_DO_GET_PAGE` | Scrape webpage using scrape.do | A tool to scrape web pages using scrape.do's API service. Makes a basic GET request to fetch webpage content while handling anti-bot protections and proxy rotation automatically. Does not execute JavaScript by default — pages requiring client-side rendering (SPAs, dynamically loaded content) will return incomplete HTML; use SCRAPE_DO_GET_RENDER_PAGE or set render=true for those cases. |
| `SCRAPE_DO_LIST_ASYNC_JOBS` | List Asynchronous Scraping Jobs | Tool to list all asynchronous scraping jobs. Returns paginated list of jobs with their status and metadata. Use when you need to retrieve job history or monitor job statuses. Supports pagination with up to 100 jobs per page. |
| `SCRAPE_DO_SCRAPE_DO_PROXY_MODE` | Use Scrape.do Proxy Mode | This tool implements the Proxy Mode functionality of scrape.do, which allows routing requests through their proxy server. It provides an alternative way to access web scraping capabilities by handling complex JavaScript-rendered pages, geolocation-based routing, device simulation, and built-in anti-bot and retry mechanisms. |
| `SCRAPE_DO_SCRAPE_URL_POST` | Scrape URL using POST method | Tool to scrape web pages using POST method via scrape.do API. Use when you need to send POST requests to target websites with custom request body data. Supports all parameters from GET endpoint plus request body customization for POST/PUT/PATCH methods. |
| `SCRAPE_DO_SEARCH_AMAZON` | Search Amazon products | Tool to search Amazon and scrape product listings with structured results. Performs keyword searches and returns structured product data including titles, prices, ratings, Prime status, sponsored flags, and position rankings in JSON format. Use when you need to search for products on Amazon marketplace or gather product information from search results. |
| `SCRAPE_DO_SET_BLOCK_URLS` | Block specific URLs during scraping | This tool allows users to block specific URLs during the scraping process. It's particularly useful for blocking unwanted resources like analytics scripts, advertisements, or any other URLs that might interfere with the scraping process or slow it down. It provides granular control by allowing users to specify URL patterns to block, thereby improving scraping performance and maintaining privacy. |
| `SCRAPE_DO_SET_REGIONAL_GEO_CODE` | Set Regional Geolocation for Scraping | This tool allows users to set a broader geographical targeting by specifying a region code instead of a specific country code. This is useful when you want to scrape content from an entire region rather than a specific country. Note that this feature requires super mode to be enabled and is only available for Business Plan or higher subscriptions. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Scrape do MCP server is an implementation of the Model Context Protocol that connects your AI agent to Scrape do. It provides structured and secure access so your agent can perform Scrape do operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Scrape do project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Scrape do.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only scrape_do.
- The router checks the user's Scrape do connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Scrape do.
- This approach keeps things lightweight and lets the agent request Scrape do tools only when needed during the conversation.
```python
# Create a Scrape do Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["scrape_do"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Scrape do
const session = await composio.create(userId as string, {
  toolkits: ['scrape_do'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Scrape do. "
        "Help users perform Scrape do operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Scrape do. Help users perform Scrape do operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

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

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["scrape_do"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Scrape do. "
        "Help users perform Scrape do operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

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

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['scrape_do'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Scrape do. Help users perform Scrape do operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Scrape do MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Scrape do.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Scrape do MCP Agent with another framework

- [Claude Agent SDK](https://composio.dev/toolkits/scrape_do/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/scrape_do/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/scrape_do/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/scrape_do/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/scrape_do/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/scrape_do/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/scrape_do/framework/cli)
- [Google ADK](https://composio.dev/toolkits/scrape_do/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/scrape_do/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/scrape_do/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/scrape_do/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/scrape_do/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/scrape_do/framework/crew-ai)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Scrape do MCP?

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

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents 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 Scrape do tools.

### Can I manage the permissions and scopes for Scrape do while using Tool Router?

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

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