The agent ecosystem is fragmenting across protocols, registries and vertical platforms. AgentSort doesn't bet on one standard — it ingests them all, then owns the layer they don't answer: the decision.
WHERE AGENTSORT SITS
LAYERPRIMARY JOBAGENTSORT POSTURE
MCPConnect models to tools and external capabilitiesIngest + invoke
MCP RegistryCatalog public MCP serversIngest
A2AAgent-to-agent capability description and communicationIngest + invoke
OpenAPI / SkillsLegacy and emerging machine-actionable interfacesNormalize
AgentSortRank, verify, route, measure and monetizeOwns the decision layer
The fundamental object isn't "an agent." The best answer to an intent may be a dedicated agent, a business API, an MCP server, or a marketplace — so AgentSort ranks Provider × Capability × Context. Sort outcomes, not labels.
AgentRank signals
Six weighted dimensions behind every score.
Score drift over time
Ranking stability as evidence accumulates.
Index freshness
Share of capabilities re-verified in 24h.
The product family
Eight products, one loop: index → rank → route → observe → exchange.
01
AgentSort Graph
Five interconnected graph layers — identity, capability, access, commercial state and observed executions — continuously refreshed, because availability, pricing, permissions and reliability change by the hour. This is the data asset everything else stands on.
02
AgentSort Search
One endpoint to find eligible capabilities for an intent — across MCP registries, ARD manifests, A2A agent cards, OpenAPI schemas, partner feeds and claimed business profiles. Ingested continuously by AgentSortBot.
03
AgentRank
The organic ranking algorithm: task-conditioned, evidence-based, and increasingly driven by observed outcomes rather than self-description. Explored in depth below.
04
AgentVerify
Independent validation of identity, endpoint ownership, permissions, security posture, capability claims, pricing accuracy and reliability. Verification pays for testing and certification — it never buys ranking.
05
AgentSort Ready
The supply-side engine. A business enters its domain, receives an Agent Readiness Score, and AgentSort generates or hosts the missing pieces: machine-readable catalogs, MCP interfaces, A2A descriptors, OpenAPI adapters, auth flows and outcome callbacks.
06
AgentSort Gateway
Search, compare, route and invoke through one interface. Assistants and independent agents connect to AgentSort once instead of integrating thousands of providers — and retain final editorial judgment over every choice.
07
AgentExchange
A commercial auction for agentic demand, priced on outcomes rather than clicks — because an agentic platform can observe the full funnel from intent to verified result. Structurally separate from organic ranking, always.
08
AgentSort Analytics
Visibility and performance analytics for providers: how agents find you, choose you, and where you lose executions — the machine-demand equivalent of search analytics.
INSIDE AGENTRANK
One global score is not enough.
An agent that is exceptional at code generation may be poor at travel booking. AgentRank evaluates every provider in the context of a task and its constraints — pick a task and watch the signal weights shift.
AgentRank(p | q, c)
The rank of provider p for task q under context c — with a recursive, PageRank-like authority component where every edge carries task, outcome, cost, latency, trust and time.
Semantic relevance
fit to intent & constraints
0.88
Historical success
comparable executions
0.92
Graph authority
trusted delegation
0.70
Trust & security
identity, permissions, incidents
0.62
Quality
output correctness
0.90
Cost / value
outcome quality vs cost
0.55
Latency / reliability
speed, uptime, failures
0.74
Freshness
recency of evidence
0.60
Availability
can it act right now
0.66
A provider with 40 lucky successes never outranks one with 40,000 reliable ones — scores are confidence-adjusted with Bayesian priors, and confidence ships alongside every estimate. Illustrative weights.
THE CROWN JEWEL
The Execution Graph
Crawler metadata is reproducible. Knowing what happened when an AI actually used each capability is not. Over time, real executions outweigh declared claims and synthetic benchmarks in the ranking model.
INTENT
A structured task with constraints — not raw conversation.
→
CANDIDATES
Eligible providers with evidence attached.
→
SELECTION
What the agent chose — and what it passed over.
→
EXECUTION
Latency, cost, errors, retries — observed live.
→
OUTCOME
Did it actually work? Signed receipts and callbacks.
More usage
Every routed execution adds an edge to the graph.
Better ranking
Observed behavior sharpens AgentRank where it matters.
Harder to replicate
The flywheel compounds into the moat.
NON-NEGOTIABLE
Organic and sponsored never mix.
AGENTRANK — ORGANIC
Ranked by evidence and outcomes
Cannot be bought, ever
Confidence shipped with every score
Returned as the primary feed
AGENTEXCHANGE — SPONSORED
Separate auction, separate feed
Priced on verified outcomes, not clicks
Minimum organic quality required to bid
Host decides whether and how to render
Payment cannot increase organic rank. The host always keeps the final choice.
Routing fan-out
Candidate selection and fallback paths.
Execution reliability
Observed success across provider cohorts.
BUILT ADVERSARIAL-FIRST
✓Signed execution receipts and host-side outcome callbacks