Brightdata MCP vs Novada MCP
A side-by-side look at the Brightdata MCP and Novada MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Brightdata MCP 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?
Choose Brightdata 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:
API_TOKEN. - You want tools like
search_engine, scrape_as_markdown, search_engine_batch.
Choose 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.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Search & Data Extraction | Search & Data Extraction |
| Quality signal | 73/100 · Great | 64/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | API key required | API key required |
| Pricing | Freemium | Not declared |
| Required env vars | API_TOKEN | NOVADA_API_KEY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 2,716 | 3 |
| Directory activity | 6 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | 11 | 37 |
| Full listing | View Brightdata MCP | View Novada MCP |
Tools & capabilities
Brightdata MCP tools 11
search_engineScrape search results from Google, Bing or Yandex. Returns SERP results in JSON or Markdown (URL, title, description),Ideal forgathering current information, news, and detailed search results.scrape_as_markdownScrape a single webpage URL with advanced options for content extraction and get back the results in MarkDown language. This tool can unlock any webpage even if it uses bot detection or CAPTCHA.search_engine_batchRun multiple search queries simultaneously. Returns JSON for Google, Markdown for Bing/Yandex.scrape_batchScrape multiple webpages URLs with advanced options for content extraction and get back the results in MarkDown language. This tool can unlock any webpage even if it uses bot detection or CAPTCHA.discoverSearch the web and rank results by AI-driven relevance. Returns scored results with title, description, and URL. Supports intent-based ranking, geo-targeting, date filtering, and keyword filtering.search_scrapersFind a Bright Data pre-built scraper (Web Scraper API, 1,200+ sites) for a site or data type, e.g. "amazon reviews" or "linkedin.com". Returns dataset_id, name, domain and collection_methods. Next: call get_scraper_details with a dataset_id and one method.get_scraper_detailsShow the scraper description, input fields, example input and main output fields for one method. Call before run_scraper and build the input from sample_input or input_fields. Records may contain more fields than output_fields lists.run_scraperRun a scraper method. input is a list of objects shaped like sample_input from get_scraper_details, one per URL or query. collect_by_url returns one record per input; discover_by_* methods return up to limit_per_input records per input, and every record is billed. Waits up to 45 seconds; if still running it returns snapshot_id with status "running": then poll get_scraper_progress and call get_scraper_results when ready. Records with an "error" field explain failed inputs.get_scraper_progressStatus of a run: starting, running, ready, failed or canceled.get_scraper_resultsRecords of a finished run. Returns status "running" if not ready yet.refresh_scrapersReload the scraper list now instead of waiting for the daily refresh.
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.
Brightdata MCP
{
"mcpServers": {
"brightdata-mcp": {
"command": "npx",
"args": [
"@brightdata/mcp"
],
"env": {
"API_TOKEN": "YOUR_API_TOKEN_HERE"
}
}
}
}
Novada MCP
{
"mcpServers": {
"novada-mcp": {
"command": "npx",
"args": [
"-y",
"novada-mcp"
],
"env": {
"NOVADA_API_KEY": "YOUR_NOVADA_API_KEY_HERE"
}
}
}
}
Frequently asked questions
Brightdata MCP 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 Brightdata MCP 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.
Brightdata MCP 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 brightdata-mcp and novada-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Brightdata MCP has a quality signal of 73/100 (Great) with 6 views, 0 installs and 2,716 GitHub stars. Novada MCP has 64/100 (Good) with 0 views, 0 installs and 3 GitHub stars.