# How to integrate Scrapfly MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Scrapfly MCP with OpenAI Agents SDK",
  "toolkit": "Scrapfly",
  "toolkit_slug": "scrapfly",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/scrapfly/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/scrapfly/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:24:48.991Z"
}
```

## Introduction

This guide walks you through connecting Scrapfly to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Scrapfly agent that can extract product prices from amazon listings, scrape job postings from linkedin search, get latest news headlines from bbc homepage through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Scrapfly account through Composio's Scrapfly MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Scrapfly with

- [Claude Agent SDK](https://composio.dev/toolkits/scrapfly/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/scrapfly/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/scrapfly/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/scrapfly/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/scrapfly/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/scrapfly/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/scrapfly/framework/cli)
- [Google ADK](https://composio.dev/toolkits/scrapfly/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/scrapfly/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/scrapfly/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/scrapfly/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/scrapfly/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/scrapfly/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 Scrapfly
- Configure an AI agent that can use Scrapfly as a tool
- Run a live chat session where you can ask the agent to perform Scrapfly 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 Scrapfly MCP server, and what's possible with it?

The Scrapfly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Scrapfly account. It provides structured and secure access to powerful web scraping capabilities, so your agent can perform actions like extracting website data, bypassing anti-bot protection, rendering JavaScript content, and rotating proxies—all on your behalf.
- Dynamic web data extraction: Instruct your agent to fetch and extract content from almost any website, even those with heavy client-side rendering or complex structures.
- JavaScript rendering support: Enable your agent to scrape websites that require full JavaScript execution for content loading, making dynamic sites accessible for data extraction.
- Anti-bot protection bypass: Allow your agent to automatically navigate sites with CAPTCHAs, bot detection, or rate limiting using Scrapfly's built-in countermeasures.
- Automatic proxy rotation: Let your agent leverage Scrapfly's proxy network to rotate requests, reduce blocks, and ensure more reliable scraping at scale.
- Custom request handling: Have your agent specify advanced options like custom headers or cookies for targeted and flexible scraping sessions.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SCRAPFLY_CAPTURE_SCREENSHOT` | Capture Website Screenshot | Tool to capture a full-page or viewport screenshot of a website. Use when you need to take a screenshot with options like JS rendering, custom resolution, or accessibility testing. Returns the screenshot image directly. Supports vision deficiency simulations and dark mode. |
| `SCRAPFLY_CAPTURE_SCREENSHOT_HEAD` | Capture Screenshot Metadata (HEAD) | Tool to capture screenshot metadata without downloading the image body. Use this for async screenshot workflows where you need the URL to retrieve the image later. Returns the screenshot URL in response, saving bandwidth compared to full screenshot retrieval. |
| `SCRAPFLY_CREATE_CRAWLER` | Create Scrapfly Crawler | Tool to create a new web crawler to recursively crawl an entire website. Returns a crawler UUID for tracking progress. Use when you need to crawl multiple pages from a website with configurable limits and extraction rules. |
| `SCRAPFLY_EXTRACT_DATA` | Extract Structured Data | Tool to extract structured data from HTML or other content using AI models, LLM prompts, or custom templates. Use when you need to parse web pages or documents into structured JSON data. Supports predefined extraction models for common types (articles, products, events) or custom extraction via prompts/templates. |
| `SCRAPFLY_GET_ACCOUNT_INFO` | Get Scrapfly Account Information | Tool to retrieve Scrapfly account information. Use after authenticating to get API credit balance and usage stats. Returns comprehensive account data including subscription plan, usage statistics, billing info, and project settings. |
| `SCRAPFLY_GET_CRAWLER_ARTIFACT` | Get Crawler Artifact | Tool to download crawler artifact files in WARC or HAR format. Use when you need to retrieve the complete crawl results as an archive file. WARC format is recommended for large crawls as it includes gzip compression. |
| `SCRAPFLY_GET_CRAWLER_CONTENTS` | Get Crawler Contents | Tool to retrieve extracted content from crawled pages. Supports multiple output formats including markdown, text, HTML, and JSON. Use when you need to access the actual content extracted during a crawl, with optional filtering by URL and format selection. |
| `SCRAPFLY_GET_CRAWLER_STATUS` | Get Crawler Status | Tool to get the current status of a crawler including progress, pages crawled, and completion state. Use for polling workflow to monitor crawl progress. |
| `SCRAPFLY_GET_CRAWLER_URLS` | Get Crawler URLs | Tool to retrieve the list of discovered and crawled URLs from a crawler. Use when you need to get all URLs found during a crawl or filter by status to analyze failed URLs with error codes. Supports pagination for large result sets. |
| `SCRAPFLY_SCRAPE` | Scrapfly Scrape | Tool to perform a web scraping request. Use when you need to fetch a page with custom configuration like JS rendering, proxies, and extraction. |
| `SCRAPFLY_SCRAPE_POST` | Scrapfly Scrape POST | Tool to scrape web pages using POST method to send data in the request body. Use when you need to scrape endpoints that require POST requests, such as form submissions or APIs that expect data payload. |
| `SCRAPFLY_SCRAPE_WITH_PUT` | Scrape With PUT | Tool to scrape web pages using PUT method with body payload. Use when the target API requires PUT requests with data in the request body. Forwards PUT request with custom body to the target URL. If not specified, content-type defaults to application/x-www-form-urlencoded. |

## Supported Triggers

None listed.

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

The Scrapfly MCP server is an implementation of the Model Context Protocol that connects your AI agent to Scrapfly. It provides structured and secure access so your agent can perform Scrapfly 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 Scrapfly 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 Scrapfly.
```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 scrapfly.
- The router checks the user's Scrapfly connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Scrapfly.
- This approach keeps things lightweight and lets the agent request Scrapfly tools only when needed during the conversation.
```python
# Create a Scrapfly Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["scrapfly"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Scrapfly
const session = await composio.create(userId as string, {
  toolkits: ['scrapfly'],
});
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 Scrapfly. "
        "Help users perform Scrapfly 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 Scrapfly. Help users perform Scrapfly 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=["scrapfly"]
)
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 Scrapfly. "
        "Help users perform Scrapfly 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: ['scrapfly'],
  });
  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 Scrapfly. Help users perform Scrapfly 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 Scrapfly MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Scrapfly.
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 Scrapfly MCP Agent with another framework

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

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

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)