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Linkup vs Tavily Search

Web Search

Linkup
Linkup
85
VS
Tavily Search
100
Tavily Search
Metric Linkup Tavily Search
Category Web Search Web Search
Pricing Freemium Freemium
Auth API Key API Key
Format JSON JSON
Bot Blocking None None
OpenAPI Spec No Yes
Credit Card Not required Not required
Rate Limit 10 req/sec per organization 1,000 req/min
Score Component Linkup Tavily Search
Base +50 +50
OpenAPI Spec 0 (No) +15 (Yes)
Auth +10 (API Key) +10 (API Key)
Format +10 (JSON) +10 (JSON)
Bot Blocking +10 (None) +10 (None)
No CC +5 (Yes) +5 (Yes)
Free 0 (No) 0 (No)
Total 85 100
Linkup Tavily Search
Pros
  • + Three output modes (searchResults, sourcedAnswer, structured) let agents pick the right format without post-processing
  • + Deep search uses agentic chain-of-thought for complex multi-step queries — top scores on SimpleQA factuality benchmark
  • + Native integrations with LangChain, CrewAI, Vercel AI SDK, and MCP server for plug-and-play agent tooling
  • + Built for LLMs — returns concise summaries, not raw HTML
  • + No separate scraper needed
  • + Native LangChain & LlamaIndex integrations
Cons
  • - Deep searches are significantly more expensive (€50/1k vs €5/1k standard) and slower due to agentic workflow
  • - Single unified endpoint — no separate crawl/sitemap/batch endpoints like some competitors
  • - Slower than raw Google Search API due to backend summarization
  • - Limited image/video search
Badges
API KeyFreemiumJSONBot Blocking: NoneNo CCsearchllm-optimizedstructured-outputsourced-answersmcp-serverreal-time
OpenAPI SpecAPI KeyFreemiumJSONBot Blocking: NoneNo CCsearchllm-optimizedmarkdown-outputreal-time

Linkup Integration

example.py
from linkup import LinkupClient
client = LinkupClient(api_key="YOUR_API_KEY")result = client.search(    query="latest AI news",    depth="standard",    output_type="sourcedAnswer")print(result)

Tavily Search Integration

example.py
from tavily import TavilyClient
client = TavilyClient(api_key="tvly-...")result = client.search("latest AI news", max_results=3)for r in result["results"]:    print(r["title"], r["url"])