A Model Context Protocol (MCP) server implementation that integrates with Firecrawl for web scraping capabilities.
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Highlight AIScrape content from a single URL with advanced options. Best for single page content extraction.
Map a website to discover all indexed URLs on the site. Best for discovering URLs on a website before deciding what to scrape.
Search the web and optionally extract content from search results. Best for finding specific information across multiple websites.
Sends structured feedback on a previous firecrawl_search result. Helps improve Firecrawl's search quality.
Sends structured feedback for a completed v2 endpoint job through /v2/feedback. Use for endpoint-level feedback on scrape, parse, map, or search jobs.
Starts a crawl job, polls until it reaches a terminal state, and returns the final crawl status/data. Best for extracting content from multiple related pages.
Check the status and results of an existing crawl job by ID.
Parse local files or hosted upload references with Firecrawl's /v2/parse endpoint. Best for parsing documents that need markdown or structured JSON output.
Extract structured information from web pages using LLM capabilities. Supports both cloud AI and self-hosted LLM extraction.
Autonomous web research agent that independently browses the internet, searches for information, navigates through pages, and extracts structured data based on your query.
Check the status of an agent job and retrieve results when complete.
Interact with a fresh URL or with a page that was already opened by firecrawl_scrape. Best for clicking, typing, navigating, and extracting state from dynamic pages.
Stop an interact session for a scraped page when you are done interacting.
Create and manage recurring page monitors that run scheduled scrapes or crawls and can notify by webhook or email.
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