MCP Server for Medium Data Extraction

Use Bright Data’s enterprise-grade MCP Server to scrape public Medium data. Extract, analyze, and process public articles, author profiles, publication details, topics, tags, reading stats, and trending stories quickly, reliably, and at scale.

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The Ultimate MCP Tool to Scrape Medium Data

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One MCP for the Web

Bright Data MCP for Medium lets you extract public articles, author profiles, tags, publication details, reading stats, and trending story data.
Search
  • Enable Claude to retrieve real-time public Medium articles, stories, and publications
  • Target specific topics, tags, or authors for curated content discovery
  • Fetch relevant articles, author profiles, and reading stats for Claude to analyze, summarize, or monitor further
Crawl
  • Let Claude crawl and extract complete stories and publication pages, not just headlines
  • Output public Medium data in Claude-ready formats for seamless LLM integration
  • Effortlessly scale article data extraction for Claude, no matter the project size
Access
  • Give Claude reliable access to any public Medium article, author, or tag data
  • Bypass geo-restrictions and CAPTCHAs automatically for uninterrupted Medium data extraction by Claude
  • Render JavaScript to retrieve dynamic story feeds and interactions for Claude's use
Navigate
  • Automate Claude agent workflows to extract Medium data from interactive story feeds and trending pages
  • Power remote browser sessions for Claude to streamline large-scale Medium scraping
  • Mimic real user behavior for Claude to bypass advanced anti-bot protections on Medium
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Medium MCP Server FAQs

The Medium MCP Server is a specialized integration that empowers your AI agents to access real-time public data from Medium. It acts as a bridge, allowing tools like Claude, Cursor, and custom LLMs to search, extract, and interact with Medium content dynamically.

Built on Bright Data's robust infrastructure, the Web MCP Server handles the complexities of web data extraction behind the scenes. It automatically manages proxy rotation, CAPTCHA solving, and unlocking technology to ensure your AI receives structured, reliable data from Medium without getting blocked.

The data is completely real-time. Unlike databases that can become outdated, the Medium MCP fetches live content directly from the source at the moment of request, ensuring your AI agents act on the most current pricing, posts, or profile information available.

Yes! We offer a generous free tier that includes 5,000 requests per month. This allows developers and businesses to test the Medium MCP Server, build prototypes, and perform light data extraction at no cost before scaling up.

Yes. Beyond retrieving static data, the server supports full browser automation. Your agents can be instructed to navigate Medium pages, click buttons, handle infinite scrolling, and even take screenshots, enabling complex workflows that simulate real user behavior.

You have the choice. You can use our fully managed Remote MCP for instant access with zero infrastructure setup, or you can deploy the Local MCP if you require on-premise control and custom environment configurations for your Medium projects.

Our Web MCP Server is designed for seamless integration with popular AI clients. It works natively with Claude Desktop, Cursor, Windsurf, and diverse agentic frameworks like LangChain, making it easy to add Medium data capabilities to your existing workflows.

Rapid mode is free and ideal for everyday tasks like SERP lookups and basic text extraction. Pro mode unlocks premium capabilities for Medium, including deep structured data extraction and advanced browser automation tools designed for large-scale production environments.

Absolutely. The Medium MCP Server is built with strict adherence to data protection regulations, including GDPR and CCPA. We only access publicly available web data, ensuring your AI operations remain compliant and ethically sound.

The server delivers data in clean, AI-ready formats. Depending on your specific needs, you can retrieve Medium data as structured JSON objects for precise analysis or as simplified Markdown text optimized for LLM context windows.