# How to integrate Scrapingant MCP with CrewAI ```json { "title": "How to integrate Scrapingant MCP with CrewAI", "toolkit": "Scrapingant", "toolkit_slug": "scrapingant", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/scrapingant/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/scrapingant/framework/crew-ai.md", "updated_at": "2026-05-12T10:24:50.976Z" } ``` ## Introduction This guide walks you through connecting Scrapingant to CrewAI using the Composio tool router. By the end, you'll have a working Scrapingant agent that can extract product prices from amazon search page, convert a blog post to markdown format, get api usage stats for your account through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Scrapingant account through Composio's Scrapingant MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Scrapingant with - [OpenAI Agents SDK](https://composio.dev/toolkits/scrapingant/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/scrapingant/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/scrapingant/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/scrapingant/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/scrapingant/framework/codex) - [OpenClaw](https://composio.dev/toolkits/scrapingant/framework/openclaw) - [Hermes](https://composio.dev/toolkits/scrapingant/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/scrapingant/framework/cli) - [Google ADK](https://composio.dev/toolkits/scrapingant/framework/google-adk) - [LangChain](https://composio.dev/toolkits/scrapingant/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/scrapingant/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/scrapingant/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/scrapingant/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Scrapingant connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Scrapingant - Build a conversational loop where your agent can execute Scrapingant operations ## What is CrewAI? CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews. Key features include: - Agent Roles: Define specialized agents with specific goals and backstories - Task Management: Create tasks with clear descriptions and expected outputs - Crew Orchestration: Combine agents and tasks into collaborative workflows - MCP Integration: Connect to external tools through Model Context Protocol ## What is the Scrapingant MCP server, and what's possible with it? The Scrapingant MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Scrapingant account. It provides structured and secure access to powerful web scraping tools, so your agent can extract web data, render dynamic pages, convert content to markdown, and monitor API usage on your behalf. - AI-powered data extraction: Direct your agent to pull structured data from web pages using custom AI queries—ideal for capturing tables, lists, prices, or other key information. - Dynamic web page scraping: Scrape complex sites with JavaScript rendering, proxy rotation, and support for cookies or browser emulation to handle modern web content. - Content conversion to markdown: Have your agent extract and convert page content into markdown format for clean, ready-to-use text in downstream applications or LLM pipelines. - Extended scraping with rich JSON output: Fetch detailed responses including raw HTML, headers, cookies, and other metadata to support advanced automation and analysis tasks. - API credit monitoring: Let your agent check and report on your current Scrapingant API credit usage, helping you manage quotas and avoid interruptions. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SCRAPINGANT_EXTRACT_CONTENT_AS_MARKDOWN` | Extract Content as Markdown | This tool extracts content from a given URL and converts it into Markdown format. It is particularly useful for preparing text for Language Learning Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. It supports GET, POST, PUT, and DELETE methods. | | `SCRAPINGANT_EXTRACT_DATA_WITH_AI` | Extract Data with AI | This tool allows you to extract structured data from a web page using ScrapingAnt's AI-powered extraction capabilities. You provide a URL and an AI query (prompt) describing what data you want to extract, and the tool returns the extracted data in a structured format. It supports additional parameters for browser rendering, proxies, and cookies to handle dynamic content and localization. | | `SCRAPINGANT_GET_API_CREDITS_USAGE` | Get API Credits Usage | This tool retrieves the current API credit usage status for the authenticated ScrapingAnt account. It enables users to monitor their consumption of API credits, check their current usage against the subscription limits, and manage their API credits effectively. | | `SCRAPINGANT_SCRAPE_WEB_PAGE` | Scrape Web Page | This tool scrapes a web page using the ScrapingAnt API. It fetches the HTML content of the specified URL. Users can customize the scraping behavior by enabling a headless browser, using proxies, waiting for specific elements, executing JavaScript, passing cookies, and blocking certain resources. | | `SCRAPINGANT_SCRAPE_WEBPAGE_POST` | Scrape Webpage via POST | Tool to perform a POST request through ScrapingAnt's proxy to scrape a webpage. Use when you need to scrape pages that require POST method, such as form submissions or APIs that only accept POST requests. Data is forwarded transparently to the target web page. | | `SCRAPINGANT_SCRAPE_WEBPAGE_PUT` | Scrape Webpage with PUT | Tool to perform a PUT request through ScrapingAnt's proxy to scrape a webpage that requires PUT method. Use when the target webpage requires PUT method for data submission. Data is forwarded transparently to the target web page. | | `SCRAPINGANT_SCRAPE_WITH_EXTENDED_JSON_OUTPUT` | Scrape with Extended JSON Output | Scrapes a web page and returns comprehensive data including HTML content, plain text, cookies, HTTP headers, XHR/Fetch requests, and iframe content. This tool uses ScrapingAnt's extended endpoint which provides much richer data than standard scraping: - Full HTML and extracted plain text content - All cookies and HTTP response headers from the target page - Captured XHR/Fetch API requests made by the page (useful for finding hidden APIs) - Content from embedded iframes Best used when you need more than just the HTML - such as analyzing cookies, headers, or JavaScript API calls made by a page. For simple HTML scraping, consider using the basic scrape tool instead for lower API credit usage. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Scrapingant MCP server is an implementation of the Model Context Protocol that connects your AI agent to Scrapingant. It provides structured and secure access so your agent can perform Scrapingant 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: - Python 3.9 or higher - A Composio account and API key - A Scrapingant connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 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). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies **What's happening:** - composio connects your agent to Scrapingant via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates with Composio - USER_ID scopes the session to your account - OPENAI_API_KEY lets CrewAI use your chosen OpenAI model ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **What's happening:** - CrewAI classes define agents and tasks, and run the workflow - MCPServerHTTP connects the agent to an MCP endpoint - Composio will give you a short lived Scrapingant MCP URL ```python import os from composio import Composio from crewai import Agent, Task, Crew from crewai_tools import MCPServerAdapter import dotenv dotenv.load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") ``` ### 5. Create a Composio Tool Router session for Scrapingant **What's happening:** - You create a Scrapingant only session through Composio - Composio returns an MCP HTTP URL that exposes Scrapingant tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["scrapingant"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **What's Happening:** - Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication. - MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format. - Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools. - Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops. - Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries. ```python server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users search the internet effectively", backstory="You are a helpful assistant with access to search tools.", tools=tools, verbose=False, max_iter=10, ) ``` ### 7. Create a CLI Chatloop and define the Crew **What's Happening:** - Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable. - Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean. - Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses. - Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context. - Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response. - Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity. ```python print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Complete Code ```python from crewai import Agent, Task, Crew, LLM from crewai_tools import MCPServerAdapter from composio import Composio from dotenv import load_dotenv import os load_dotenv() 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.") # Initialize Composio and create a session composio = Composio(api_key=COMPOSIO_API_KEY) session = composio.create( user_id=COMPOSIO_USER_ID, toolkits=["scrapingant"], ) url = session.mcp.url # Configure LLM llm = LLM( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY"), ) server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users with internet searches", backstory="You are an expert assistant with access to Composio Search tools.", tools=tools, llm=llm, verbose=False, max_iter=10, ) print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Conclusion You now have a CrewAI agent connected to Scrapingant through Composio's Tool Router. The agent can perform Scrapingant operations through natural language commands. Next steps: - Add role-specific instructions to customize agent behavior - Plug in more toolkits for multi-app workflows - Chain tasks for complex multi-step operations ## How to build Scrapingant MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/scrapingant/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/scrapingant/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/scrapingant/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/scrapingant/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/scrapingant/framework/codex) - [OpenClaw](https://composio.dev/toolkits/scrapingant/framework/openclaw) - [Hermes](https://composio.dev/toolkits/scrapingant/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/scrapingant/framework/cli) - [Google ADK](https://composio.dev/toolkits/scrapingant/framework/google-adk) - [LangChain](https://composio.dev/toolkits/scrapingant/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/scrapingant/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/scrapingant/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/scrapingant/framework/llama-index) ## 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 Scrapingant MCP? With a standalone Scrapingant MCP server, the agents and LLMs can only access a fixed set of Scrapingant tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Scrapingant and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with CrewAI? Yes, you can. CrewAI 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 Scrapingant tools. ### Can I manage the permissions and scopes for Scrapingant while using Tool Router? Yes, absolutely. You can configure which Scrapingant 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 Scrapingant data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)