ALPNAI

ALPNAI is a Swiss‑based SaaS platform that provides economic and performance analysis for AI agents. It offers tools such as Spend Proof, Latency Lab, and Quality Gate to measure cost per successful task, latency, and quality thresholds. Users can compare configurations, generate audit reports, and integrate the service via its API. The product is developed in Geneva by Frederic Pure and targets developers and teams deploying AI agents.

ALPNAI is listed with 1 API on the APIs.io network. Tagged areas include Artificial Intelligence, Software-as-a-Service, Performance, Analytics, and Swiss.

ALPNAI’s developer surface includes documentation, API reference, getting-started guide, pricing, and 12 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

16.7/100 emerging ▼ -6.6 Agent 4/100 human only Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemium

1 API 1 MCP Servers

Artificial Intelligence Software-as-a-Service Performance Analytics Swiss

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 16.7/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 2.4 / 17

Access Clarity 6.3 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.5 / 10

Discoverability 5.2 / 9

Regulatory Posture 2.0 / 15

Agent readiness — 4/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0

12 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 14.3 — up to +17.1 composite points
Operational Transparency scores 0.0 — up to +13.0 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/alpnai-com/apis.yml: open an issue on github.com/api-evangelist/alpnai-com to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Model Context Protocol (MCP)

measured — observed by APIs.io (documented)

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

ALPNAI Agent API

ALPNAI Agent API for analyzing AI-agent measurements.

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

ALPNAI MCP Server

Remote MCP server at alpnai.com.

MCP SERVER

ALPNAI API pricing

Prices published by ALPNAI, read 2026-11-01 from alpnai.com/fr/plans.

Plan	Price
Découverte	0 USD
Projects Pro	19 USD/ mois

Plan details, limits and sources →

Pricing Plans 1

Published pricing tiers and plan structures.

Alpnai Com Plans Pricing

2 plans

PLANS

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Alpnai Com Domain Security

TLSv1.3 · DNSSEC

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

MCPServer

MCPServer

WellKnown

WellKnown

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Commercial 4

Pricing, plans, and the legal terms of use

Plans

TermsOfService

PrivacyPolicy

Pricing

Company 2

The organization behind the API

Website

Website

About

About

Other 2

Properties that don't map to a standard resource type

Hosts

Hosts

Vendors

Vendors

Source (apis.yml)

aid: alpnai-com
name: ALPNAI
description: ALPNAI is a Swiss‑based SaaS platform that provides economic and performance analysis for AI agents. It offers
  tools such as Spend Proof, Latency Lab, and Quality Gate to measure cost per successful task, latency, and quality thresholds.
  Users can compare configurations, generate audit reports, and integrate the service via its API. The product is developed
  in Geneva by Frederic Pure and targets developers and teams deploying AI agents.
url: https://artifacts.apis.io/alpnai-com/apis.yml
x-type: company
x-source: harvest:mcp-registry
x-tier: profiled
x-tier-reason: enrichment pass 2026-11-01 (modular-v1; was harvest)
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-06'
  method: derived
specificationVersion: '0.20'
created: '2026-11-01'
modified: '2026-11-01'
tags:
- Artificial Intelligence
- Software-as-a-Service
- Performance
- Analytics
- Swiss
tags_raw:
- AI
- SaaS
- Performance
- Analytics
- Swiss
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Plans
  url: plans/alpnai-com-plans-pricing.yml
- type: Conformance
  url: conformance/alpnai-com-conformance.yml
- type: LLMsTxt
  url: llms/alpnai-com-llms.txt
- type: MCPServer
  url: mcp/alpnai-com-mcp.yml
- type: WellKnown
  url: well-known/alpnai-com-well-known.yml
- type: Hosts
  url: hosts/alpnai-com-hosts.yml
- type: Vendors
  url: vendors/alpnai-com-vendors.yml
- type: TermsOfService
  url: https://alpnai.com/fr/legal/terms
- type: PrivacyPolicy
  url: https://alpnai.com/fr/legal/privacy
- type: DomainSecurity
  url: security/alpnai-com-domain-security.yml
- type: Website
  url: https://alpnai.com/
- type: Documentation
  url: https://alpnai.com/fr/docs
- type: APIReference
  url: https://alpnai.com/fr/docs/api
- type: GettingStarted
  url: https://alpnai.com/fr/docs/quickstart
- type: Pricing
  url: https://alpnai.com/fr/plans
- type: About
  url: https://alpnai.com/fr/about
apis:
- name: ALPNAI Agent API
  description: ALPNAI Agent API for analyzing AI-agent measurements.
  humanURL: https://alpnai.com/fr/docs/api
  baseURL: https://alpnai.com
  aid: alpnai-com:alpnai-agent-api
x-enrichment:
  date: '2026-11-01'
  status: enriched
  artifacts_added: 13
  pass: modular-v1
  engine: identity=local,contract=local,surfaces=local,docs=local,regulatory=local

ALPNAI API — frequently asked questions

Does ALPNAI have an API?

Yes. APIs.io lists 1 API from ALPNAI, including ALPNAI Agent API.

How much does the ALPNAI API cost?

ALPNAI publishes its prices; its Découverte plan is 0 USD as of 2026-11-01. APIs.io lists 2 pricing plans for ALPNAI, with each plan's price, limits and inclusions under Pricing on this page.

Does ALPNAI have an MCP server?

Yes. APIs.io lists 1 MCP server for ALPNAI: Remote MCP server at alpnai.com.

Is the ALPNAI API ready for AI agents?

ALPNAI has a Kin Score of 16.7 out of 100 (emerging) and an Agent Readiness score of 3.5 (human-only), scored by API Evangelist on 2026-11-06.

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

9 MCP tools reach this

find_providersBrowse and filter every provider in the catalog.
get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

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