Firecrawl MCP Server vs Novada MCP

A side-by-side look at the Firecrawl MCP Server and Novada MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Firecrawl MCP Server logoFirecrawl MCP ServerSearch & Data Extraction · Local subprocess (stdio)Official Firecrawl server to search the web and scrape, crawl, map, and extract structured data from any site for LLMs. Handles JS-rendered pages, PDFs, and batch jobs; hosted remote MCP with OAuth or self-host.90ExcellentAuth: api key requiredNovada MCP logoNovada MCPSearch & Data Extraction · Local subprocess (stdio)Search, extract, crawl, map, research, scrape 16 platforms, browser automation, proxy — one API key.64GoodAuth: api key required

Verdict: choose Firecrawl MCP Server for search & data extraction work as a local process; choose Novada 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?

Firecrawl MCP Server logoChoose 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.
  • You want tools like firecrawl_scrape, firecrawl_map, firecrawl_search.
Explore Firecrawl MCP Server

Novada MCP logoChoose Novada MCP 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: NOVADA_API_KEY.
  • You want tools like novada_search, novada_extract, novada_crawl.
Explore Novada MCP

Feature & specification comparison

Rows where the two servers differ are marked.

SpecFirecrawl MCP Server logoFirecrawl MCP ServerNovada MCP logoNovada MCP
CategorySearch & Data ExtractionSearch & Data Extraction
Quality signal90/100 · Excellent64/100 · Good
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthAPI key requiredAPI key required
PricingFreemiumNot declared
Required env varsFIRECRAWL_API_KEYNOVADA_API_KEY
Verified owner VerifiedCommunity listing
GitHub stars7,7803
Directory activity 33 views 3 installs 0 upvotes 0 views 0 installs 0 upvotes
Tools2537

Tools & capabilities

Firecrawl MCP Server tools 25

  • firecrawl_scrape Retrieve 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_map Enumerate 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_search Search 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_crawl Start 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_status Retrieve 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_extract Deprecated 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_agent Start 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_status Retrieve 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_interact Open 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_stop Stop the live interact session associated with a `scrapeId` and release its resources. Returns a success confirmation.
  • firecrawl_parse Parse 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_create Create 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

Novada MCP tools 37

  • novada_searchSearch the web for clean, ready-to-use content — titles, URLs, snippets, reranked by relevance. For multi-source questions, use novada_research instead (faster, more thorough). **Use for:** current events, URL lookup, fact-checking, competitive research. enrich_top=true auto-extracts the #1 result. **Not for:** a known URL (novada_extract) or a multi-source report (novada_research). **Tip:** engine='google' (default) is fastest/most reliable; duckduckgo/yandex are slower fallbacks. **Domain filtering:** includeDomains/excludeDomains inject `site:domain` into the query (not API-side). **Project grouping:** `project="my-project"` groups outputs under a subfolder (~/Downloads/novada-mcp/<date>/<project>/).
  • novada_extractExtract content from any URL. Auto-handles Cloudflare/DataDome/Kasada via escalation (static → JS render → Browser CDP). Batch mode: pass url as an array for up to 10 pages in parallel. **Format selection:** - `format="markdown"` (default): full-page content for reading/analysis. - `format="json"`: structured object (url, title, content, quality, links, structured_data, fields, hints, mode, fetched_at). Use with `fields=["price","title"]` to populate `fields`. Common mistake: using markdown when you need specific fields — use format="json"+fields instead. - `format="html"`: raw HTML (truncated at 100K chars by default; adjust via max_chars). - `clean=true`: strip nav/sidebar, main content only (~15K chars vs ~100K full page). **Use for:** reading pages, batch-extracting search results, structured fields (price, author, date) — works on anti-bot pages automatically. **Not for:** URL discovery (novada_map), multi-page crawl (novada_crawl), rich platform data like Amazon/LinkedIn (novada_scrape). **Key rule:** leave render="auto" (default) — 15-100x faster on static sites; only set render="render" for known JS-heavy SPAs. **Geo-routing:** `country="de"` (ISO 2-letter) routes render fetches through that country's exit IP — for localized pricing or geo-restricted content. **Auto-saved:** every extraction is written to `~/Downloads/novada-mcp/YYYY-MM-DD/` (path shown in the response). **Project grouping:** `project="my-project"` groups outputs under a subfolder.
  • novada_crawlUse when you need content from a bounded set of pages (up to 20) and don't have the URLs yet. Crawls BFS/DFS, extracts each page inline. Use select_paths globs to target sections (e.g. "/docs/api/**"). **Wrong tool for whole-site jobs:** for >20 pages or a full docs site on disk, use `novada_site_copy` instead (up to 1000 pages, streams to disk, returns a manifest). novada_crawl hard-caps at 20 pages and returns bodies inline. **Best for:** competitive content analysis, a handful of related pages inline (returns bodies directly). **Not for:** a single page (novada_extract), URL discovery only (novada_map — much faster), a whole site to disk (novada_site_copy). **Performance:** avoid max_pages > 10 on large sites — crawl time scales ~1.4s/page (max_pages=20 ≈ 28s minimum). Use select_paths to narrow scope before raising max_pages. **Rendering:** `render` defaults to "auto" (static first, escalates to JS on detection) — not static-only.
  • novada_researchOne call → 3-10 parallel searches across Google/Bing/DuckDuckGo → dedup → extracts full content from top sources → returns CITED SOURCE MATERIAL (numbered passages), not a written answer. Extractive, not generative — you compose the final answer from the gathered passages. **Use for:** complex questions needing passages from ≥3 independent sources in one call — comparative analysis, market research, technical deep dives, competitive intelligence. Replaces 5-10 manual search+extract calls. **Not for:** a single fact or one URL (novada_search — faster/cheaper), a known URL (novada_extract), or a finished prose report (this returns source material, not an answer). **Depth:** "quick" (3 queries), "deep" (6), "comprehensive" (8-9), "auto" (default — quick or deep by question length, never comprehensive). **Project grouping:** `project="my-project"` groups outputs under a subfolder. **Recency:** `time_range` ("day"|"week"|"month"|"year"), `start_date`/`end_date` (ISO YYYY-MM-DD) propagate to every internal search call. **Response size:** extracts full content from the top 5 sources only (even at depth="comprehensive"); each source is capped at novada_extract's own default 25,000-char limit — bounded total, not unbounded "every source in full."
  • novada_mapDiscover URLs on a site before deciding what to read. Tries sitemap.xml first (fast), falls back to BFS crawl. Returns URLs only — no content. Hard cap: 100 URLs. **Best for:** site structure discovery, finding the right subpage, pre-flight before novada_crawl/novada_extract. **Not for:** reading content (use novada_crawl/novada_extract) or copying a whole site to disk (novada_site_copy). **Note:** limited results on JS SPAs — flagged in the output.
  • novada_site_copyCopy an entire docs site/section to disk as clean markdown — one.md file per page — returning a COMPACT manifest, not page bodies. Use for a whole knowledge base on disk (offline docs ingest, RAG corpus, full-site mirror). **Discovery order:** (1) llms.txt/llms-full.txt if present, (2) sitemap.xml, (3) scoped same-host BFS to completion. select_paths/exclude_paths and same-host are always enforced. **Best for:** "copy all of docs.x.com", a local docs corpus, ingesting an llms.txt index. **Not for:** a single page (novada_extract), a few pages inline (novada_crawl), URL discovery only (novada_map). **Output:** each page streams to `~/Downloads/novada-mcp/<date>/<project|domain>/site-copy/<slug>.md`; `manifest.json` records {url,file,title,word_count,depth,bytes,status} per page. The tool returns a compact summary + manifest path, not inline content — read the.md files or manifest.json after it completes. **Scale:** max_pages default 200, hard max 1000, drained until the queue is empty or the ceiling is hit.
  • novada_scrapeUse for structured data from a specific platform — clean tabular records, not raw HTML. Proxies the Novada Scraper API (scraper.novada.com; public docs: https://developer.novada.com/novada/advanced-proxy-solutions/scraper-api/target-sites-supported-by-scraper-api). Supports 14 platforms (~76 operations): Google, LinkedIn, Amazon, YouTube, Walmart, DuckDuckGo, TikTok, Bing, Instagram, X (Twitter), Facebook, Perplexity AI, Yandex, GitHub. **Best for:** e-commerce product data, social posts/comments, job listings, reviews, real estate, market data. **Not for:** general web pages outside this platform list — use novada_extract instead. **Prefer the dedicated tool when one exists:** for amazon/google/bing/duckduckgo/yandex/youtube/instagram/facebook/tiktok/x/walmart/linkedin/github/perplexity, call novada_scrape_<platform> instead — same engine, but its `operation` enum uses typed friendly names and is rejected client-side before any network call if wrong. Use THIS generic tool for platforms with no dedicated sibling or when resuming by task_id. **Output formats:** markdown (default table), json (records array inside a fenced "## Scrape Results" block), toon (pipe-separated, 40-65% smaller — best for large result sets), csv, excel (base64), html. **Example:** platform="amazon.com", operation="amazon_product_keywords", params={keyword:"iphone 16", num:5}. **Amazon price fields:** trust `final_price`/`price` (check `_price_source`) — `initial_price` and `buybox_prices.final_price` are often 0 by design, not a bug; `buybox_prices.unit_price` is raw per-unit data, never the listing price. **Discover platforms:** read the `novada://scraper-platforms` resource for the full, always-current operation list (slugs + required params), or see the public reference at https://developer.novada.com/novada/advanced-proxy-solutions/scraper-api/target-sites-supported-by-scraper-api. **Resume:** pass `task_id` from a prior status:processing call to fetch the result without a new billable task (platform/operation still required, display-only). **Project grouping:** `project="my-project"` groups outputs under a subfolder.
  • novada_scrape_amazonExtract structured Amazon data — product details, reviews, seller info, bestseller lists, category/brand listings — via a closed, typed `operation` enum (same engine as novada_scrape, pinned to platform="amazon.com"). **Use when:** "get the price/rating/title for Amazon ASIN B0...", "pull the reviews for this Amazon product URL", "search Amazon for <keyword> with price and rating", "who is this Amazon seller", "what's in this Amazon Best Sellers list". **Not for:** Any other platform — use its own novada_scrape_<platform> tool, or novada_scrape(platform="<domain>"). A general Google/web search — use novada_search. Reading one arbitrary URL's raw content — use novada_extract. **Returns:** Structured product/review/seller records (title, price, rating, asin, availability, etc.) in the chosen output format — same rendering as novada_scrape. **Ops:** 10 verified-working Amazon operations. 3 known backend-broken ones are excluded from this enum (rejected client-side before any backend call) — unlike novada_scrape(platform="amazon.com",...), which still forwards them with a warning.
  • novada_scrape_googleExtract structured Google SERP data — organic web search, AI Mode answers, Maps place/review details, Shopping, Jobs, Hotels, Videos — via a closed, typed `operation` enum (same engine as novada_scrape, pinned to platform="google.com"). Returns raw structured SERP records, not a generated answer. **Use when:** "get the raw Google search results (titles, links, ranks) for <query>", "what's in Google's AI Mode answer for <query>", "pull Google Maps reviews or place details for this URL / place_id / CID", "search Google Shopping for <keyword>", "find Google Jobs, Hotels, or Videos results for <query>". **Not for:** A general question needing just an answer or a few good links — use novada_search (multi-engine: google/duckduckgo/yandex, ranked/reranked, cheaper than a raw-SERP scrape). A complex question needing cited multi-source synthesis — use novada_research. Reading one already-known URL's page content — use novada_extract. A different platform's data — use its own novada_scrape_<platform> tool, or novada_scrape(platform="<domain>"). **Returns:** Structured SERP records per operation — organic results (title/url/snippet/rank), AI Mode answer content, Maps place details/reviews, Shopping listings (price/rating), Jobs/Hotels/Videos listings — in the chosen output format, same rendering as novada_scrape. **Ops:** 13 verified-working Google operations spanning web search, AI Mode, Maps (location/place_id/CID/URL lookups + reviews), Shopping, Jobs, Hotels, and Videos. Every google.com catalog operation is currently status:"ok" — none are excluded for being backend_broken.
  • novada_scrape_bingExtract structured Bing SERP data — organic web search, video results, news results, shopping listings — via a closed, typed `operation` enum (same engine as novada_scrape, pinned to platform="bing.com"). Bing is NOT a selectable engine on novada_search — this is the only intentional way to query Bing specifically. **Use when:** "get the raw Bing search results (titles, links, ranks) for <query>", "find Bing video results for <query>", "find Bing news results for <query>, sorted by date", "search Bing Shopping for <keyword>". **Not for:** A general question needing just an answer or a few good links — use novada_search — google/duckduckgo/yandex only (Bing is not selectable there); ranked, cheaper than a raw-SERP scrape. A complex question needing cited multi-source synthesis — use novada_research. Reading one already-known URL's page content — use novada_extract. A different platform's data — use its own novada_scrape_<platform> tool, or novada_scrape(platform="<domain>"). **Returns:** Structured SERP records per operation — organic results (title/url/snippet/rank), video results, news results (with date), shopping listings (price/rating) — in the chosen output format, same rendering as novada_scrape. **Ops:** 4 verified-working Bing operations: web search, videos, news, and shopping. Every bing.com catalog operation is currently status:"ok" — none are excluded for being backend_broken.
  • novada_scrape_duckduckgoExtract structured DuckDuckGo web search SERP data via a closed, typed `operation` enum (same engine as novada_scrape, pinned to platform="duckduckgo.com"). Returns the raw organic-results SERP, with region/time/adult-content filters novada_search does not expose, not a generated answer. **Use when:** "get the raw DuckDuckGo search results (titles, links, ranks) for <query>", "search DuckDuckGo restricted to a specific region (params.kl) or time range (params.df)", "compare DuckDuckGo's ranking for <query> against another engine's raw SERP". **Not for:** A general question needing just an answer or a few good links — use novada_search with engine="duckduckgo" (ranked/reranked instead of a raw SERP dump). A complex question needing cited multi-source synthesis — use novada_research. Reading one already-known URL's page content — use novada_extract. A different platform's data — use its own novada_scrape_<platform> tool, or novada_scrape(platform="<domain>"). **Returns:** Structured organic-result SERP records (title/url/snippet/rank) in the chosen output format, same rendering as novada_scrape. **Ops:** 1 verified-working DuckDuckGo operation (web search). The single duckduckgo.com catalog operation is currently status:"ok".
  • novada_scrape_yandexExtract structured Yandex web search SERP data via a closed, typed `operation` enum (same engine as novada_scrape, pinned to platform="yandex.com"). Returns the raw organic-results SERP, with TLD/language/time-range controls novada_search does not expose, not a generated answer. **Use when:** "get the raw Yandex search results (titles, links, ranks) for <query>", "search a specific Yandex TLD (params.yandex_domain, e.g. "yandex.ru") for Russian/Eastern European content", "search Yandex restricted to a time range (params.within)". **Not for:** A general question needing just an answer or a few good links — use novada_search with engine="yandex" (ranked/reranked instead of a raw SERP dump). A complex question needing cited multi-source synthesis — use novada_research. Reading one already-known URL's page content — use novada_extract. A different platform's data — use its own novada_scrape_<platform> tool, or novada_scrape(platform="<domain>"). **Returns:** Structured organic-result SERP records (title/url/snippet/rank) in the chosen output format, same rendering as novada_scrape. **Ops:** 1 verified-working Yandex operation (web search, requires params.yandex_domain TLD selector). The single yandex.com catalog operation is currently status:"ok".
  • +25 more on the listing page

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 (Claude Desktop / Cursor)
{
  "mcpServers": {
    "firecrawl-firecrawl-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "firecrawl-mcp"
      ],
      "env": {
        "FIRECRAWL_API_KEY": "YOUR_FIRECRAWL_API_KEY_HERE"
      }
    }
  }
}

Novada MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "novada-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "novada-mcp"
      ],
      "env": {
        "NOVADA_API_KEY": "YOUR_NOVADA_API_KEY_HERE"
      }
    }
  }
}

Frequently asked questions

Firecrawl MCP Server is categorized under Search & Data Extraction and uses a local stdio subprocess. Novada MCP belongs to Search & Data Extraction and uses a local stdio subprocess. Pick Firecrawl MCP Server for search & data extraction work and Novada 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. Novada MCP has no declared pricing — check the project's own site. Auth: api key required. 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 novada-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 33 views, 3 installs and 7,780 GitHub stars. Novada MCP has 64/100 (Good) with 0 views, 0 installs and 3 GitHub stars.