Firecrawl MCP Server

The Firecrawl MCP Server bridges the powerful web‑scraping engine of Firecrawl with AI assistants that speak Model Context Protocol (MCP). By exposing scraping, crawling, and content‑extraction capabilities as MCP tools, the server allows conversational agents to pull fresh data from the web on demand, without developers writing custom HTTP clients or handling authentication. This solves a common pain point for AI‑driven research and data pipelines: retrieving reliable, structured information from arbitrary URLs while respecting rate limits and retry logic.

At its core, the server provides a set of declarative actions—such as “crawl a site,” “extract article text,” or “discover links”—that an assistant can invoke by sending a simple JSON request. The server internally talks to Firecrawl’s API, manages retries and rate limiting automatically, and streams results back via Server‑Sent Events (SSE) for real‑time feedback. Developers can host the server on their own infrastructure or in the cloud, and it integrates seamlessly with popular MCP clients like Cursor, Windsurf, VS Code, and even the experimental Streamable HTTP local mode.

Key capabilities include:

• Web scraping & crawling: Fetch pages, follow links, and build site maps in a single operation.
• Content extraction: Pull structured data (titles, authors, publication dates) or raw article bodies.
• Batch scraping: Process large lists of URLs efficiently with built‑in concurrency controls.
• Automatic retries & rate limiting: Protect against transient failures and respect API quotas without manual tuning.
• SSE support: Stream progress updates to the client, enabling responsive UI or incremental prompt construction.

Typical use cases span from market‑research bots that gather competitor pricing to academic assistants that aggregate recent papers. In a workflow, an assistant might first ask a user for a topic, then invoke the Firecrawl server to crawl relevant news sites, extract article summaries, and return a concise briefing. Because the server is an MCP endpoint, any AI platform that understands the protocol can consume it out of the box, making it a drop‑in extension for existing tools.

Unique advantages lie in its tight coupling with Firecrawl’s mature scraping engine and the convenience of SSE streaming. Developers benefit from a single, well‑documented MCP interface rather than juggling multiple scraping libraries or handling authentication tokens manually. The server’s support for both cloud and self‑hosted deployments ensures flexibility across security requirements, while the integration guides for Cursor, Windsurf, and VS Code lower the barrier to entry for rapid experimentation.