One scraper API for every social, search, e-commerce and real estate platform.
Connect your AI Agent to real-time data from Google Search, LinkedIn, Reddit, TikTok, Instagram, Amazon, Walmart and many more.
50 free credits · no credit card
Live demo
One request. structured JSON.
Point one key at any platform — no OAuth, no quota audit. The same call your crons and your agents make in production.
1{2 "search_parameters": {3 "query": "What are the latest updates with Nvidia?",4 "engine": "google",5 "device": "desktop"6 },7 "search_information": {8 "total_results": 48200000,9 "time_taken": 0.4210 },11 "organic_results": [12 {13 "position": 1,14 "title": "What are the latest updates with Nvidia?",15 "link": "https://en.wikipedia.org/wiki/...",16 "snippet": "Overview and the latest developments, updated continuously..."17 },18 {19 "position": 2,20 "title": "Latest news and analysis",21 "link": "https://www.reuters.com/...",22 "snippet": "Breaking coverage from the past 24 hours..."23 }24 ],25 "related_searches": [26 "latest updates",27 "2026 roadmap"28 ],29 "response_time": 0.94,30 "credits_used": 1,31 "credits_remaining": 4932}native to the agent stack you already run
/ why builders switch
Built for the platforms that gated their API.
One key, every walled platform
YouTube quotas, TikTok's approval wall, Reddit's $12k/yr floor, Instagram's dead Basic Display API. One key keeps returning clean, structured data from all of them.
Made for recurring pipelines
Creator monitors, price trackers, research agents. Structured JSON on a schedule, with failover across upstream providers so your unattended crons don't break.
Agent-native, pay as you go
MCP, LangChain, OpenAI Agents SDK, Vercel AI SDK, Agno, CrewAI, n8n and 10+ more integrations your agents call directly. No minimums, no seats.
/ pricing
Start free. Pay only for what you use.
Every plan includes every platform. 50 free credits on signup — no credit card required.
Free
For getting started
No credit card required
Start with 50 free credits- credits on signup
- 50
- per credit
- $0
- requests per second
- 1
All platforms included
Project
For side projects
$288 billed once a year
Save $72 a year
- credits every month
- 7,000
- per credit
- $0.0034
- requests per second
- 5
Email support
Bootstrap
Most popularFor growing products
$948 billed once a year
Save $252 a year
- credits every month
- 28,000
- per credit
- $0.0028
- requests per second
- 10
Email support
Startup
For scaling teams
$2,388 billed once a year
Save $612 a year
- credits every month
- 85,000
- per credit
- $0.0023
- requests per second
- 15
Priority support
Growth
For high-volume usage
$4,788 billed once a year
Save $1,212 a year
- credits every month
- 200,000
- per credit
- $0.0020
- requests per second
- 50
Priority support
Need something else?
Why do AI agents need real-time search?
Large language models are trained on static data with a knowledge cutoff. When an AI agent needs current prices, live inventory, trending videos, community sentiment on Reddit, or today's news, it has to pull that data in real time. A scraper API like Scavio gives agents structured access to YouTube, TikTok, Reddit, Instagram, Google, Amazon, and Walmart so they can make decisions based on what's happening now, not months ago.
What is Scavio?
Scavio is a scraper API built for AI agents and developers. One API pulls structured data from YouTube, TikTok, Reddit, Instagram, Google, Amazon, and Walmart, returning clean JSON instead of raw HTML. Agents get titles, URLs, descriptions, prices, post scores, comments, and metadata they can act on immediately. No browser automation, no proxy management, no scraping infrastructure of your own to maintain.
How do AI agents use Scavio for research and decision-making?
An AI agent sends Scavio a query and a target platform, and gets back structured results it can reason over. A shopping agent compares prices across Amazon and Walmart in a single workflow. A research agent pulls Google results, YouTube tutorials, and Reddit discussions on the same topic for multi-source grounding. A brand-monitoring agent tracks Reddit mentions and sentiment in near real time. Scavio handles the search infrastructure so the agent focuses on its task.
How is Scavio different from Tavily, SerpAPI, or Google Custom Search?
Most search APIs only return Google results. Scavio covers YouTube, TikTok, Reddit, Instagram, Google, Amazon, and Walmart from one API, so agents can pull social, search, and ecommerce data without managing seven different integrations. Responses are structured JSON optimized for AI consumption, not raw SERP HTML. Pricing starts at 1 credit per request with a free tier of 50 credits on signup.
What can I build with a multi-platform search API?
Developers use Scavio to build AI shopping assistants that compare prices across Amazon and Walmart, research agents that pull information from Google, YouTube, and Reddit, RAG pipelines that ground LLM responses in real-time web and community data, competitive intelligence tools that track products and Reddit chatter across marketplaces, and content recommendation engines powered by live search results.
How does real-time search improve RAG pipelines?
Retrieval-Augmented Generation works best when the retrieved data is current and relevant. Scavio provides real-time results from multiple platforms, so your RAG pipeline can ground LLM outputs in live web data rather than a static knowledge base. This is critical for queries about current events, product availability, pricing, or any domain where information changes frequently.
Which AI agent frameworks work with Scavio?
Scavio works with any framework that can make HTTP requests: LangChain, CrewAI, AutoGen, OpenAI Assistants, custom agents, and more. The API is a single POST endpoint that returns JSON, so there are no framework-specific SDKs to install. Most developers connect their agents to Scavio in under 10 minutes.
Why search Amazon, YouTube, Walmart, and Reddit instead of just Google?
Google gives you web pages, but many AI agent tasks need specialized data. Product research needs real prices and reviews from Amazon and Walmart. Video discovery needs YouTube metadata like view counts and upload dates. Community signal and unfiltered opinions live on Reddit, which also acts as a leading indicator for what AI Overviews will cite next. A multi-platform search API lets agents access the right data source for each task instead of trying to extract everything from Google links.
What is MCP and how does Scavio support it?
MCP (Model Context Protocol) is an open standard for connecting AI assistants to external tools and data. Scavio runs an MCP server at mcp.scavio.dev/mcp that exposes 11 tools covering Google Search, Amazon, Walmart, YouTube, and Reddit. Any MCP-compatible client -- including Claude Code, Claude Desktop, Cursor, Windsurf, VS Code, ChatGPT, Cline, and Zed -- can connect with a single JSON config. No code required, setup takes under 2 minutes.
Which AI assistants work with Scavio via MCP?
Scavio's MCP server works with Claude Code, Claude Desktop, Cursor, Windsurf, VS Code (GitHub Copilot), ChatGPT, Cline, Zed, and any other tool that supports the Model Context Protocol. The server uses HTTP transport so there is nothing to install locally -- your AI assistant connects directly over the network. Once connected, it gets access to 11 tools for searching Google, Amazon, Walmart, YouTube, and Reddit.
Is there a free tier?
Yes. Scavio offers a free plan with 50 credits on signup and no credit card required. Each search request costs 1 credit regardless of platform. This is enough to build and test an AI agent integration, run a small production project, or evaluate whether multi-platform search adds value to your workflow. Paid plans start from $24/mo billed yearly, or $30 month to month.
How does Scavio handle data freshness?
Every Scavio API call returns live results fetched in real time from the target platform. There is no caching layer or stale index. When your agent searches Amazon, it gets current prices and availability. When it searches YouTube, it gets the latest uploads. When it searches Reddit, it gets the latest posts, scores, and comments. This makes Scavio ideal for use cases where accuracy depends on recency: price monitoring, trend detection, inventory tracking, community sentiment, and news aggregation.