The capability retrieval engine for AI.

AgentSort discovers, verifies and ranks the few capabilities a frontier model should consider for every intent. We retrieve the candidates. Your model keeps the judgment.

Frontier AI has a retrieval problem.

An AI with 20 tools can reason about them directly. An AI with access to 20 million capabilities cannot. AgentSort dynamically retrieves the few capabilities that matter for the current intent.

From a capability universe to a dynamic toolset.

AgentSort Resolve turns a massive capability universe into a small, evidence-rich toolset a frontier model can reason over efficiently — assembled per intent, discarded after.

const result = await agentsort.resolve({
  intent: "Find and book a reliable emergency
           plumber in Brooklyn tonight",
  top_k: 5,
  constraints: {
    verified: true,
    available_within: "2 hours",
    required_verification_level: 3
  }
});

The toolset is assembled per intent.

AgentSort composes a capability set on demand for each intent, then lets it go. Nothing needs to stay permanently loaded in the model’s context.

Built for ChatGPT, Claude, Gemini
and the next frontier model.

One call gives a frontier model everything it needs to decide which capability to invoke.

One API instead of rebuilding the agentic internet.

Recreating capability retrieval internally means owning and continuously operating every one of these systems.

Discovery is not the hard part. Trust is.

The question is no longer “can I find an agent?” — it is “can I trust the thing I am about to let an AI invoke?” AgentVerify is a four-level ladder, independently assessed.

required_verification_level >= 3

Claims tell us what an agent says it can do.
Outcomes tell us what it actually does.

Registries tell AgentSort what providers claim. The Execution Graph records what actually happens when those capabilities are invoked — across platforms, not inside one.

A neutral-data network effect.

Each integrated platform benefits from aggregated evidence generated across the wider ecosystem — without exposing any platform’s private data to another.

Connect once. Reach every protocol.

Connect once to AgentSort and dynamically discover capabilities across MCP, A2A, ARD, APIs, Agent Skills and future protocols. AgentSort handles discovery, normalization, verification and ranking so your AI does not have to.

Five linked graphs, one answer.

For this precise intent, under these constraints, which provider is most likely to successfully accomplish the task right now?

Google solved information retrieval.
AgentSort solves capability retrieval.

Open standards solve publication.
Abundance creates the need for sorting.

Organic ranking is never for sale.

AgentExchange is a separate commercial feed a host platform may choose to surface and label. Money can never improve organic AgentRank.

Credibility first. Commerce after.

AgentExchange only becomes powerful after AgentSort earns ranking credibility. The commercial model evolves beyond cost per click toward cost per outcome.

One layer, three constituencies.

The same problem, inside the firewall.

Large enterprises are accumulating internal agents and tools faster than any team can catalogue them. Which internal capability should our AI use?

Can AI find your business?

Make sure AI can find you, choose you and transact with you.

Why this layer becomes inevitable.