Herramienta de IABecomes the API

Linkup

Premium web search API for AI agents. OpenAPI plus per-query pricing.

shipped 26 may 2026analyzefreemium

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Stork Quadrant

Becomes the API· 25/100

Replaceable as a UI, but kept alive as the API the agents call.

“Linkup is a thin wrapper around web search. Claude and other LLMs can already call Brave, Google, or Bing search APIs directly, or agents can use built-in web search. The only defensibility is speed or result quality, but those decay as models get native search. This dies unless Linkup becomes the default search layer that agents prefer — which requires either better results than free APIs or a network effect it doesn't have.”
— Claude Haiku 4.5, scored 2026-05-27

Defensibility · 0/100

Physical-world coupling
Regulatory moat
Network liquidity
Proprietary refreshing data
High-trust catastrophic workflows
Multi-party coordination
Brand / community / taste

An LLM alone could replace

Fetch and parse web search results for an agent query
Return structured data about web pages (title, snippet, URL)
Rate-limit and meter API calls to control cost
Integrate search into an agentic workflow via OpenAPI spec

Agent-Readiness · 55/100

Verified MCP
Listed on agent surfaces— anthropic_directory
Usage-based pricing— pricing page heuristic match: https://linkup.so/pricing
Headless agent auth
Public OpenAPI— https://api.linkup.so/v1/openapi.json
Active changelog— https://linkup.so/blog (2026-05-25)
llms.txt

Score history · +14 pts over 2 re-scores

How to defend

Become the search backbone for agent frameworks (like LangChain or CrewAI) by offering 10x cheaper per-query pricing and proving result quality on agent-specific benchmarks. Or pivot to vertical search (legal, medical, financial) where proprietary indexing and regulatory trust matter.

Ship an MCP server and list it on Stork — biggest single point gain (+25).
Expose API-key auth with a self-serve sandbox tier; remove sales-call gates (+15).
Ship an /llms.txt file pointing agents to your most important docs (+5, easy win).

How this score is computed →See the full quadrant How to defend

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