Real-time web access. No black box.
A Tavily alternative for AI agents that need direct, transparent web access — your search engine, your URLs, your output format. Fetch any page as HTML, Markdown, or plain text. Scrape the SERPs you trust. Build the agent loop the way you'd build any other backend, with no vendor-side reranking layer.
10,000 free credits · failed requests cost 0 · works with any MCP client
// claude_desktop_config.json
{
"mcpServers": {
"scrapingant": {
"url": "https://api.scrapingant.com/mcp",
"transport": "streamableHttp",
"headers": {
"x-api-key": "YOUR_API_KEY"
}
}
}
}# One command. Same MCP server.
$ claude mcp add scrapingant \
--transport http \
https://api.scrapingant.com/mcp \
-H "x-api-key: YOUR_API_KEY"
✓ scrapingant added · 3 tools registered# Inside the agent — the loop runs on YOUR side:
1. search Google for "best vector DBs for RAG"
→ get_web_page_html("https://google.com/search?q=…")
2. parse SERP, agent picks 5 URLs
→ ['pinecone.io/blog', 'qdrant.tech/docs', …]
3. fetch each one as Markdown
→ get_web_page_markdown(url) × 5
4. your code chunks, embeds, indexes — your call.# Skip MCP, hit the same API directly from any language.
$ curl -G "https://api.scrapingant.com/v2/markdown" \
--data-urlencode "url=https://example.com" \
-H "x-api-key: YOUR_API_KEY"
{
"url": "https://example.com",
"markdown": "# Example Domain\n\nThis domain…",
"status_code": 200
}Why pure web access.
Three principles that show up in every agent we see succeed in production.
No black box
Your agent picks the URLs. Your code chooses the format. No hidden filtering or proprietary reranking between query and answer.
See the workflow →Any format you need
HTML for parsing. Markdown for LLM context. Plain text for analysis. Same call, different output — pick what fits the next step.
Tool details →Anti-bot built in
Headless Chrome, rotating proxies, TLS fingerprinting, CAPTCHA avoidance — same stack that powers /v2/general.
Your agent runs the whole loop.
Agents that succeed in production are the ones whose authors can audit every step. With ScrapingAnt, search is just an HTTP request to a SERP. URL selection is logic you wrote. Fetching is a single tool call. Processing is whatever your stack already does. Nothing in the middle is “magic.”
- Pick the search engine — Google, Bing, DuckDuckGo, internal indexes
- Decide which URLs to follow with code you can debug
- Choose
html,markdown, ortextper call — same key, same auth
Pick the format your agent needs.
Same URL, same auth, three outputs. Each tool takes optional browser, proxy_type, and proxy_country parameters — LLM-ready Markdown for context, HTML for parsing, plain text for cheap summarisation. Your agent picks per call from the prompt. Need typed JSON keyed to a plain-English schema instead of raw page content? Stack with the AI data scraper.
- Markdown stripped of nav, ads, scripts — token-efficient context
- HTML preserved when you need the DOM in the agent
- Plain text for cheap summarisation passes
Same cluster. Same uptime.
Every MCP call rides the same headless Chrome cluster, rotating residential and datacenter proxies, CAPTCHA avoidance, TLS fingerprinting, and automatic retries that back the JavaScript rendering API. The MCP server is just a thinner transport on top — same SLA, same proxy fleet, same anti-bot reliability.
- 50K+ datacenter IPs, 2M+ residential — handles anti-bot out of the box
- Switch to
residentialviaproxy_typefor tougher targets - Country-pin requests with
proxy_countryacross 25+ countries - Failed requests cost zero credits — never pay for a broken page
Where teams ship it.
Six concrete patterns where direct web access changes what the agent can do.
RAG pipelines
Fetch real-time web data for retrieval-augmented generation. Pull docs, blogs, or news as clean Markdown — chunk and embed into your vector store directly.
Talk to us →AI agent research
Let agents browse the web autonomously — search, evaluate sources, extract what they need. You wire the loop; ScrapingAnt fetches the pages.
Talk to us →Live SERP scraping
Scrape Google, DuckDuckGo, or Bing search pages as live context for your LLMs. Your agent sees the same results a human searcher would.
Talk to us →Documentation fetching
Pull any docs site as clean Markdown into your AI context. Coding assistants quote today's API, not last year's training data.
Talk to us →Real-time market data
Build agents that watch pricing pages, status pages, or product feeds. Schedule recurring fetches and let your code react to diffs.
Talk to us →Custom search workflows
Build vertical-specific search — patents, GitHub repos, scientific abstracts, internal indexes — with the engine and ranking that fit your domain.
Talk to us →What will web access cost?
Three sliders. We pick the matching plan and show what your monthly bill looks like.
Pricing
Industry leading pricing that scales with your business.
|
Plans
|
Enthusiast
100K credits / mo
$19/mo
|
★ Most Popular
Startup
500K credits / mo
$49/mo
|
Business
3M credits / mo
$249/mo
|
Business Pro
8M credits / mo
$599/mo
|
Custom
10M+ credits / mo
$699+/mo
|
|---|---|---|---|---|---|
| Monthly API credits | 100,000 | 500,000 | 3,000,000 | 8,000,000 | 10M+ |
| Support channel | Priority email | Priority email | Priority email | Priority + dedicated | |
| Integration help | Docs only | Custom code snippets | Debug sessions | Priority debug sessions | Full enterprise onboarding |
| Expert assistance | — |  |
|
|
|
| Custom proxy pools | — | — | |
|
|
| Custom anti-bot avoidances | — | — | |
|
|
| Dedicated account manager | — | — | |
|
|
| Start Free | Start Free → | Start Free | Start Free | Talk to Sales |
What teams are saying.
From solo developers shipping side projects to enterprise pipelines at Fortune 500s.
★★★★★ 5.0 on Capterra →★★★★★“Onboarding and API integration was smooth and clear. Everything works great. The support was excellent.”
★★★★★“Great communication with co-founders helped me to get the job done. Great proxy diversity and good price.”
★★★★★“This product helps me to scale and extend my business. The setup is easy and support is really good.”
Frequently asked questions.
Still curious? Get in touch with our team — we usually reply within hours.
What is a Tavily alternative for AI agents?
A Tavily alternative is a web-access layer for AI agents that gives you the raw primitives — SERP scraping, URL fetching, multiple output formats — instead of a turnkey curated search API. Where Tavily ships a single query → reranked-results endpoint, ScrapingAnt gives your agent direct browser access: scrape google.com/search?q=… or duckduckgo.com/?q=…, pick the URLs, fetch each as HTML / Markdown / text. The agent runs the loop and sees what a human searcher would. Same primitives are exposed through the ScrapingAnt MCP server for Claude / Cursor / Windsurf and as a direct HTTP API for any other code.
How is this different from Tavily?
Different shape, different fit. Tavily ships a turnkey search API — you send a query, you get curated, reranked results. ScrapingAnt gives you the raw primitives: scrape any SERP, pick your URLs, fetch any page as HTML / Markdown / text. Your agent runs the loop and sees what a human searcher would. Pick whichever matches how much of the pipeline you want to own.
Can I use this for RAG pipelines?
That's the headline use case. get_web_page_markdown returns clean LLM-ready Markdown — chunk it, embed it, store it. You decide what to index — docs, blogs, news, support content. No black-box reranking; the chunks that hit your vector store are the ones you chose.
How do I search the web with ScrapingAnt MCP?
You scrape the SERP. Fetch google.com/search?q=…, duckduckgo.com/?q=…, or bing.com/search?q=… as HTML or Markdown, parse the result list, hand the URLs back to your agent. No vendor-side reranking — your agent sees the same results a human searcher would. The same approach works inside Claude Code via claude mcp add or via Cursor / Windsurf / Cline through the MCP server.
What about rate limits and anti-bot protection?
Handled. ScrapingAnt fronts every request with 50K+ datacenter IPs plus 2M+ residential IPs, real headless Chrome (the same engine behind our JavaScript rendering API), TLS fingerprinting, automatic retries, and CAPTCHA avoidance. For tougher targets, switch proxy_type to residential on the same call — no separate plan needed for the API call layer.
How do credits work for different request types?
Transparent and per-request: SERP scrape = 10 credits, JS-rendered page fetch = 10 credits, static page fetch = 1 credit, residential proxy adds a multiplier. Failed requests cost 0. Every account starts with 10,000 free credits per month, no card required. Use the calculator above to model your own usage.
Which AI tools support MCP for web access?
Anything that speaks Model Context Protocol — Claude Desktop, Cursor, VS Code (with GitHub Copilot), Claude Code (CLI), Cline, Windsurf. Same MCP URL, different config files. Setup guides for each →
Can I use this outside of MCP (direct API)?
Yes. The MCP server is one interface to ScrapingAnt's core Web Scraping API. Hit /v2/general, /v2/markdown, or /v2/extract directly from Python, Node, Go, Ruby, curl — anything that speaks HTTP. API docs →
How is this different from a Google search API?
Direct, transparent, and unmediated. Google search APIs (Custom Search JSON, SerpAPI, etc.) give you a vendor-curated subset of results in a vendor-defined shape. With ScrapingAnt, your agent fetches the actual SERP HTML or Markdown, parses it itself, and chooses which URLs to follow — no reranking layer, no quota on which sources are visible. The trade-off: you write the parser. The win: full pipeline ownership and the ability to switch search engines (Google → DuckDuckGo → Bing) by changing one URL.
Need a custom plan?
High-volume pricing, residential pool tuning, dedicated infrastructure, custom scrapers — drop us a line and a real human gets back within a few hours.
“Our clients are pleasantly surprised by the response speed of our team.”
