Firecrawl MCP Server vs ScrapeGraphAI Scrapegraph MCP
A side-by-side look at the Firecrawl MCP Server and ScrapeGraphAI Scrapegraph MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Firecrawl MCP Server for search & data extraction work as a local process; choose ScrapeGraphAI Scrapegraph MCP for search & data extraction as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Firecrawl MCP Server when
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
FIRECRAWL_API_KEY, HTTP_STREAMABLE_SERVER. - You want tools like
firecrawl_scrape, firecrawl_map, firecrawl_search.
Choose ScrapeGraphAI Scrapegraph MCP when
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
SGAI_API_KEY. - You want tools like
markdownify, smartscraper, searchscraper.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Search & Data Extraction | Search & Data Extraction |
| Quality signal | 90/100 · Excellent | 59/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | API key required | Not declared |
| Pricing | Freemium | Not declared |
| Required env vars | FIRECRAWL_API_KEYHTTP_STREAMABLE_SERVER | SGAI_API_KEY |
| Verified owner | Verified | Community listing |
| GitHub stars | 7,676 | 116 |
| Directory activity | 15 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 25 | 8 |
| Full listing | View Firecrawl MCP Server | View ScrapeGraphAI Scrapegraph MCP |
Tools & capabilities
Firecrawl MCP Server tools 25
firecrawl_scrapeRetrieve and extract content from one supplied URL through Firecrawl. Use this when the request identifies a page and needs its content or defined fields. It can return markdown, HTML, links, screenshots, branding data, a targeted answer, or JSON matching a supplied schema; JSON is useful when the requested result has defined fields, while markdown preserves readable page content. This tool operates on a known page. For a set of pages use `firecrawl_crawl`, and to discover page URLs use `firecrawl_map` or `firecrawl_search`. Options include JavaScript render delay, cache age, main-content filtering, PII redaction, and lockdown cache-only retrieval. Browser actions may change the live page when interactive actions are enabled. Firecrawl may reuse recently indexed content instead of refetching the page, and the reuse window varies by domain. Set `maxAge: 0` to force a live fetch, or a smaller `maxAge` to bound how stale reused content may be. A successful response does not by itself confirm that the state it describes is still current. Returns the selected content formats and page metadata.firecrawl_mapEnumerate URLs indexed under one website through Firecrawl without fetching each page's content. Use this when the request asks for a site's URL inventory, when several relevant pages must be located, or when the desired page URL is unknown. An optional `search` term narrows the URL list, while sitemap, subdomain, query-parameter, and result-limit options control coverage. Returns matching URLs rather than page bodies. Retrieve one page with `firecrawl_scrape`; collect content across multiple pages with `firecrawl_crawl`.firecrawl_searchSearch web, news, or image sources and return ranked results. Operators include quoted phrases, `-term`, `site:host`, `inurl:term`, `intitle:term`, and `related:host`; the set is non-exhaustive. `includeDomains` and `excludeDomains` are mutually exclusive hostname filters; categories limit results to GitHub, research, PDF, or developer sources. For a programming question, add `categories: ["developer"]`. It searches an index of GitHub issues, merged pull requests, repository READMEs, and curated documentation sites, and returns the hits in `data.developer` beside the web results. `categories: ["research"]` restricts these web results to research-affiliated websites and returns page snippets. The `firecrawl_research_*` tools are a separate surface that searches paper abstracts and full text across biomedical (PubMed, bioRxiv, medRxiv) and arXiv literature. `scrapeOptions` can attach extracted page content; pages fetched this way use a fixed reuse window and ignore `maxAge`, so use `firecrawl_scrape` when a live fetch is required. Returns source-type result groups and usage metadata. Authenticated responses can include an `id` for optional search feedback.firecrawl_crawlStart a multi-page crawl at a website URL, poll it to a terminal state, and return the final status and collected data. Scope can be bounded with include/exclude paths, depth, page limit, subdomain/external-link controls, sitemap handling, delay, and scrape options. Crawl results can be large; use conservative limits when full-site coverage is unnecessary. Webhooks and interactive scrape actions are unavailable in safe mode. Returns the crawl ID, status, and page data.firecrawl_check_crawl_statusRetrieve the current status, progress, and available results for an existing crawl ID. This only reads Firecrawl job state and does not start or modify the crawl.firecrawl_extractDeprecated compatibility entry point. Use firecrawl_scrape once per known URL with formats: ["json"] and jsonOptions containing the prompt and schema. Use firecrawl_search or firecrawl_agent before Scrape when URLs are not known.firecrawl_agentStart an asynchronous web research job from a prompt, optional seed URLs, and an optional JSON schema. Use this for a requested synthesis across multiple sources when the task can wait for asynchronous completion. The agent can search, navigate, read pages, and assemble a structured result. This call returns only a job ID, not the research result. Read the job with `firecrawl_agent_status` until it reaches `completed` or `failed`; research commonly takes several minutes. If the job cannot finish within the task's available time, `firecrawl_search` and `firecrawl_scrape` can gather evidence synchronously.firecrawl_agent_statusRetrieve progress or final results for a `firecrawl_agent` job ID. A `processing` response is non-terminal and does not contain the final research result. Check again after 15–30 seconds until the status is `completed` or `failed`; complex jobs can take several minutes. If the job cannot finish within the task's available time, use `firecrawl_search` and `firecrawl_scrape` to complete the requested output. Returns job status, progress information, and result data when completed.firecrawl_interactOpen or reuse a live browser session to navigate a page, click controls, fill fields, or run browser code. Provide either `url` or `scrapeId`, and either a natural-language `prompt` or executable `code`; code can run as Bash, Python, or Node with a bounded timeout. This acts on the live site, so actions such as form submission can create persistent external side effects. Returns execution output, stdout/stderr, exit status, and session viewing URLs.firecrawl_interact_stopStop the live interact session associated with a `scrapeId` and release its resources. Returns a success confirmation.firecrawl_parseParse one supported document into markdown, HTML, links, summary, targeted answers, or JSON matching a schema. Supported inputs include common HTML, PDF, Word, RTF, OpenDocument, and spreadsheet files; PDF parsing can be bounded with `pdfOptions.maxPages`. Local MCP reads `filePath` from the server filesystem. Hosted MCP uses two calls: first provide `filePath` to receive upload instructions, upload locally, then call again with the returned `uploadRef`; do not send both fields together. Remote web URLs belong in `firecrawl_scrape`. Set `redactPII` to request redaction of personally identifiable information in the returned content. `zeroDataRetention` requires an eligible authenticated account; omit it for anonymous keyless use. Returns upload instructions for hosted phase one or parsed document content for the final call.firecrawl_monitor_createCreate a recurring scrape, crawl, or search monitor that compares each check with its retained predecessor. The simple form accepts `page`/`pages` or `queries` plus a plain-language `goal`; the advanced `body` form controls targets, schedule, change-tracking formats, judging, retention, webhook, and notifications. In the simple form, a `goal` is required. If `queries` contains one or more non-empty values and is supplied with `page`/`pages`, `queries` create the search target and page targets are ignored. A monitor schedules future network checks and can send configured email or webhook notifications. Returns the created monitor.- +13 more on the listing page
ScrapeGraphAI Scrapegraph MCP tools 8
markdownifyConvert a webpage into clean, formatted markdown. This tool fetches any webpage and converts its content into clean, readable markdown format. Useful for extracting content from documentation, articles, and web pages for further processing. Costs 2 credits per page. Read-only operation with no side effects.smartscraperExtract structured data from a webpage, HTML, or markdown using AI-powered extraction. This tool uses advanced AI to understand your natural language prompt and extract specific structured data from web content. Supports three input modes: URL scraping, local HTML processing, or local markdown processing. Ideal for extracting product information, contact details, article metadata, or any structured content. Costs 10 credits per page. Read-only operation. Args: user_prompt (str): Natural language instructions describing what data to extract. - Be specific about the fields you want for better results - Use clear, descriptive language about the target data - Examples: * "Extract product name, price, description, and availability status" * "Find all contact methods: email addresses, phone numbers, and social media links" * "Get article title, author, publication date, and summary" * "Extract all job listings with title, company, location, and salary" - Tips for better results: * Specify exact field names you want * Mention data types (numbers, dates, URLs, etc.) * Include context about where data might be located website_url (Optional[str]): The complete URL of the webpage to scrape. - Mutually exclusive with website_html and website_markdown - Must include protocol (http:// or https://) - Supports dynamic and static content - Examples: * https://example.com/products/item * https://news.site.com/article/123 * https://company.com/contact - Default: None (must provide one of the three input sources) website_html (Optional[str]): Raw HTML content to process locally. - Mutually exclusive with website_url and website_markdown - Maximum size: 2MB - Useful for processing pre-fetched or generated HTML - Use when you already have HTML content from another source - Example: "<html><body><h1>Title</h1><p>Content</p></body></html>" - Default: None website_markdown (Optional[str]): Markdown content to process locally. - Mutually exclusive with website_url and website_html - Maximum size: 2MB - Useful for extracting from markdown documents or converted content - Works well with documentation, README files, or converted web content - Example: "# Title ## Section Content here..." - Default: None output_schema (Optional[Union[str, Dict]]): JSON schema defining expected output structure. - Can be provided as a dictionary or JSON string - Helps ensure consistent, structured output format - Optional but recommended for complex extractions - Examples: * As dict: {'type': 'object', 'properties': {'title': {'type': 'string'}, 'price': {'type': 'number'}}} * As JSON string: '{"type": "object", "properties": {"name": {"type": "string"}}}' * For arrays: {'type': 'array', 'items': {'type': 'object', 'properties': {...}}} - Default: None (AI will infer structure from prompt) number_of_scrolls (Optional[int]): Number of infinite scrolls to perform before scraping. - Range: 0-50 scrolls - Default: 0 (no scrolling) - Useful for dynamically loaded content (lazy loading, infinite scroll) - Each scroll waits for content to load before continuing - Examples: * 0: Static content, no scrolling needed * 3: Social media feeds, product listings * 10: Long articles, extensive product catalogs - Note: Increases processing time proportionally total_pages (Optional[int]): Number of pages to process for pagination. - Range: 1-100 pages - Default: 1 (single page only) - Automatically follows pagination links when available - Useful for multi-page listings, search results, catalogs - Examples: * 1: Single page extraction * 5: First 5 pages of search results * 20: Comprehensive catalog scraping - Note: Each page counts toward credit usage (10 credits × pages) render_heavy_js (Optional[bool]): Enable heavy JavaScript rendering for dynamic sites. - Default: false - Set to true for Single Page Applications (SPAs), React apps, Vue.js sites - Increases processing time but captures client-side rendered content - Use when content is loaded dynamically via JavaScript - Examples of when to use: * React/Angular/Vue applications * Sites with dynamic content loading * AJAX-heavy interfaces * Content that appears after page load - Note: Significantly increases processing time (30-60 seconds vs 5-15 seconds) stealth (Optional[bool]): Enable stealth mode to avoid bot detection. - Default: false - Helps bypass basic anti-scraping measures - Uses techniques to appear more like a human browser - Useful for sites with bot detection systems - Examples of when to use: * Sites that block automated requests * E-commerce sites with protection * Sites that require "human-like" behavior - Note: May increase processing time and is not 100% guaranteed Returns: Dictionary containing: - extracted_data: The structured data matching your prompt and optional schema - metadata: Information about the extraction process - credits_used: Number of credits consumed (10 per page processed) - processing_time: Time taken for the extraction - pages_processed: Number of pages that were analyzed - status: Success/error status of the operation Raises: ValueError: If no input source provided or multiple sources provided HTTPError: If website_url cannot be accessed TimeoutError: If processing exceeds timeout limits ValidationError: If output_schema is malformed JSONsearchscraperPerform AI-powered web searches with structured data extraction. This tool searches the web based on your query and uses AI to extract structured information from the search results. Ideal for research, competitive analysis, and gathering information from multiple sources. Each website searched costs 10 credits (default 3 websites = 30 credits). Read-only operation but results may vary over time (non-idempotent).smartcrawler_initiateInitiate an asynchronous multi-page web crawling operation with AI extraction or markdown conversion. This tool starts an intelligent crawler that discovers and processes multiple pages from a starting URL. Choose between AI Extraction Mode (10 credits/page) for structured data or Markdown Mode (2 credits/page) for content conversion. The operation is asynchronous - use smartcrawler_fetch_results to retrieve results. Creates a new crawl request (non-idempotent, non-read-only). SmartCrawler supports two modes: - AI Extraction Mode: Extracts structured data based on your prompt from every crawled page - Markdown Conversion Mode: Converts each page to clean markdown formatsmartcrawler_fetch_resultsRetrieve the results of an asynchronous SmartCrawler operation. This tool fetches the results from a previously initiated crawling operation using the request_id. The crawl request processes asynchronously in the background. Keep polling this endpoint until the status field indicates 'completed'. While processing, you'll receive status updates. Read-only operation that safely retrieves results without side effects.scrapeFetch raw page content from any URL with optional JavaScript rendering. This tool performs basic web scraping to retrieve the raw HTML content of a webpage. Optionally enable JavaScript rendering for Single Page Applications (SPAs) and sites with heavy client-side rendering. Lower cost than AI extraction (1 credit/page). Read-only operation with no side effects.sitemapExtract and discover the complete sitemap structure of any website. This tool automatically discovers all accessible URLs and pages within a website, providing a comprehensive map of the site's structure. Useful for understanding site architecture before crawling or for discovering all available content. Very cost-effective at 1 credit per request. Read-only operation with no side effects.agentic_scrapperExecute complex multi-step web scraping workflows with AI-powered automation. This tool runs an intelligent agent that can navigate websites, interact with forms and buttons, follow multi-step workflows, and extract structured data. Ideal for complex scraping scenarios requiring user interaction simulation, form submissions, or multi-page navigation flows. Supports custom output schemas and step-by-step instructions. Variable credit cost based on complexity. Can perform actions on the website (non-read-only, non-idempotent). The agent accepts flexible input formats for steps (list or JSON string) and output_schema (dict or JSON string) to accommodate different client implementations.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Firecrawl MCP Server
{
"mcpServers": {
"firecrawl-firecrawl-mcp-server": {
"command": "npx",
"args": [
"-y",
"firecrawl-mcp"
],
"env": {
"FIRECRAWL_API_KEY": "YOUR_FIRECRAWL_API_KEY_HERE",
"HTTP_STREAMABLE_SERVER": "YOUR_HTTP_STREAMABLE_SERVER_HERE"
}
}
}
}
ScrapeGraphAI Scrapegraph MCP
{
"mcpServers": {
"scrapegraphai-scrapegraph-mcp": {
"command": "uvx",
"args": [
"scrapegraph-mcp"
],
"env": {
"SGAI_API_KEY": "YOUR_SGAI_API_KEY_HERE"
}
}
}
}
Frequently asked questions
Firecrawl MCP Server is categorized under Search & Data Extraction and uses a local stdio subprocess. ScrapeGraphAI Scrapegraph MCP belongs to Search & Data Extraction and uses a local stdio subprocess. Pick Firecrawl MCP Server for search & data extraction work and ScrapeGraphAI Scrapegraph MCP for search & data extraction.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Firecrawl MCP Server is listed as freemium — a free tier with paid plans. Auth: api key required. ScrapeGraphAI Scrapegraph MCP has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add firecrawl-firecrawl-mcp-server and scrapegraphai-scrapegraph-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Firecrawl MCP Server has a quality signal of 90/100 (Excellent) with 15 views, 0 installs and 7,676 GitHub stars. ScrapeGraphAI Scrapegraph MCP has 59/100 (Good) with 1 views, 0 installs and 116 GitHub stars.