AfterQuery

AfterQuery is a San Francisco applied research lab that curates expert reasoning data for frontier foundation models - supervised fine-tuning sets, rubric- and verifier-based reinforcement-learning environments, tool-calling and computer-use environments, RLHF, deep research tasks, multimodal data, and custom evaluation suites - produced with a network of verified professionals in finance, healthcare, law and software engineering through its AfterQuery Experts contributor platform. It publishes the IDE-Bench, App-Bench, Market-Bench, FinanceArena and FinanceQA benchmarks and sells data and evaluation engagements directly to AI labs and enterprises. AfterQuery ships no public product API: its only machine-callable surface is an anonymous documentation MCP server on its help-centre host, alongside an A2A agent card, a published agent skill and two llms.txt files.

AfterQuery is listed with 1 API on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine Learning, Training Data, and Data.

AfterQuery’s developer surface includes documentation, engineering blog, support, signup flow, authentication, and 20 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

24.4/100 emerging ▬ flat Agent 21/100 agent aware Front door AI 5/6 prominent Heartbeat 100/100 alive Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

1 API 1 MCP Servers 1 Agent Skills

Company Artificial Intelligence Machine Learning Training Data Data Evaluation Reinforcement Learning Benchmarks Research Agents MCP A2A

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 24.4/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 6.1 / 17

Access Clarity 5.6 / 17

Operational Transparency 0.5 / 11

Contract Governance 1.9 / 10

Discoverability 6.4 / 9

Regulatory Posture 2.6 / 15

Agent readiness — 21/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 8 / 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 Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link Ask about this →
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document Ask about this →

8 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 Ask about this →
Access Clarity scores 33.0 — up to +13.4 composite points Ask about this →
Developer Ergonomics scores 35.7 — up to +12.9 composite points Ask about this →

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.

Not sure how this applies to your stack? Ask about any one item. Kin Lane reads every question, looks at your profile and your situation, and replies with what a fix would take — scoped to that one area, priced up front, yours whether you ship it or not. Ask a question →

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/afterquery/apis.yml: open an issue on github.com/api-evangelist/afterquery 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 3

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.

Agent2Agent

measured — observed by APIs.io (conformant)

Model Context Protocol (MCP)

measured — observed by APIs.io (documented)

Agent Skills

measured — observed by APIs.io (published)

APIs 1

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

AfterQuery Experts Help Center MCP

A read-only Model Context Protocol server over the AfterQuery Experts Help Center, served anonymously from AfterQuery's documentation host. Three tools - full-text documentation...

MCP Servers 1

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

AfterQuery Experts Help Center MCP

A read-only documentation MCP server over the AfterQuery Experts Help Center - full-text search across the help centre, a sandboxed read-only filesystem view of the documentatio...

MCP SERVER

Agent Skills 1

Packaged agent skills for driving this provider's APIs from an AI assistant.

Afterqueryexperts

AGENT SKILL

AfterQuery API pricing

Pricing Plans 1

Published pricing tiers and plan structures.

AfterQuery Plans Pricing

0 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

AfterQuery Rate Limits

0 limits

RATE LIMITS

Terms of Service 1

What its API terms permit and prohibit, quoted from its own page.

AfterQuery

5 quoted statements, read from AfterQuery's own page on 2026-11-09.

TERMS

Privacy & Data 1

Its role, the data it processes, retention and transfers, quoted from its own privacy page.

AfterQuery

13 quoted statements, read from AfterQuery's own page on 2026-11-09.

PRIVACY

Data License 1

How its data and outputs may be reused, quoted from its own terms.

AfterQuery

1 quoted statement, read from AfterQuery's own page on 2026-11-09.

LICENSE

Security Posture 2

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

AfterQuery Authentication

1 scheme

SECURITY

AfterQuery Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

SignUp

SignUp

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

MCPServer

AgentSkill

LLMsTxt

WellKnown

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Conventions

Conventions

Conformance

Conformance

Build 2

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Operate 4

Status, limits, changes, and where to get help

Support

HelpCenter

RateLimits

Contact

Commercial 5

Pricing, plans, and the legal terms of use

TermsOfService

PrivacyPolicy

Plans

UsageTerms

DataLicense

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 2

Properties that don't map to a standard resource type

AgentCard

AgentCard

DataProcessing

DataProcessing

Source (apis.yml)

aid: afterquery
name: AfterQuery
description: 'AfterQuery is a San Francisco applied research lab that curates expert reasoning data for frontier foundation
  models - supervised fine-tuning sets, rubric- and verifier-based reinforcement-learning environments, tool-calling and computer-use
  environments, RLHF, deep research tasks, multimodal data, and custom evaluation suites - produced with a network of verified
  professionals in finance, healthcare, law and software engineering through its AfterQuery Experts contributor platform.
  It publishes the IDE-Bench, App-Bench, Market-Bench, FinanceArena and FinanceQA benchmarks and sells data and evaluation
  engagements directly to AI labs and enterprises. AfterQuery ships no public product API: its only machine-callable surface
  is an anonymous documentation MCP server on its help-centre host, alongside an A2A agent card, a published agent skill and
  two llms.txt files.'
url: https://raw.githubusercontent.com/api-evangelist/afterquery/refs/heads/main/apis.yml
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - rate-limits
  - security
  generated: '2026-11-13'
  method: derived
image: https://www.afterquery.com/og-default.png
x-type: company
x-source: harvest:secondary-market
specificationVersion: '0.20'
created: '2026-09-12'
modified: '2026-09-12'
x-docs-platform: mintlify
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-09-17
x-docs-hosting: vercel
tags:
- Company
- Artificial Intelligence
- Machine Learning
- Training Data
- Data
- Evaluation
- Reinforcement Learning
- Benchmarks
- Research
- Agents
- MCP
- A2A
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Training Data
- Data
- Evaluations
- Reinforcement Learning
- Benchmarks
- Research
- Agents
- Model Context Protocol
- Machine-Learning
- A2A
apis:
- aid: afterquery:afterquery-experts-help-center-mcp
  name: AfterQuery Experts Help Center MCP
  description: A read-only Model Context Protocol server over the AfterQuery Experts Help Center, served anonymously from
    AfterQuery's documentation host. Three tools - full-text documentation search, a sandboxed read-only filesystem view of
    the help-centre pages, and documentation feedback submission - verified live by an unauthenticated tools/list on 2026-09-12.
    It is a documentation-platform surface generated by Mintlify, not an interface to AfterQuery's data, evaluation or research
    products, which have no public API.
  humanURL: https://docs.afterquery.com/
  baseURL: https://docs.afterquery.com/mcp
  image: https://www.afterquery.com/og-default.png
  tags:
  - MCP
  - Documentation
  - Agents
  tags_raw:
  - Model Context Protocol
  - Documentation
  - Agents
  properties:
  - type: Documentation
    url: https://docs.afterquery.com/
  - type: MCPServer
    url: mcp/afterquery-mcp.yml
  - type: AgentCard
    url: a2a/afterquery-a2a.yml
  - type: AgentSkill
    url: skills/_index.yml
  - type: Authentication
    url: authentication/afterquery-authentication.yml
  - type: Conventions
    url: conventions/afterquery-conventions.yml
  - type: RateLimits
    url: rate-limits/afterquery-rate-limits.yml
common:
- type: DomainSecurity
  url: security/afterquery-domain-security.yml
- type: Website
  url: https://www.afterquery.com/
- type: Documentation
  url: https://docs.afterquery.com/
- type: Blog
  url: https://www.afterquery.com/blog
- type: Support
  url: https://www.afterquery.com/contact
- type: HelpCenter
  url: https://docs.afterquery.com/report-a-bug
- type: SignUp
  url: https://experts.afterquery.com/apply
- type: GitHubOrganization
  url: https://github.com/AfterQuery
- type: TermsOfService
  url: https://www.afterquery.com/terms
- type: PrivacyPolicy
  url: https://www.afterquery.com/privacy
- type: MCPServer
  url: mcp/afterquery-mcp.yml
- type: AgentCard
  url: a2a/afterquery-a2a.yml
- type: AgentSkill
  url: skills/_index.yml
- type: LLMsTxt
  url: llms/afterquery-llms.txt
- type: WellKnown
  url: well-known/afterquery-well-known.yml
- type: Authentication
  url: authentication/afterquery-authentication.yml
- type: Conventions
  url: conventions/afterquery-conventions.yml
- type: Conformance
  url: conformance/afterquery-conformance.yml
- type: Plans
  url: plans/afterquery-plans-pricing.yml
- type: RateLimits
  url: rate-limits/afterquery-rate-limits.yml
- type: Packages
  url: packages/afterquery-packages.yml
- type: Contact
  url: mailto:sales@afterquery.com
- type: UsageTerms
  url: terms/afterquery-terms-of-service.yml
- type: DataProcessing
  url: privacy/afterquery-privacy-policy.yml
- type: DataLicense
  url: data-license/afterquery-data-license.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-09-12'
  status: enriched
  artifacts_added: 17
  pass: local-v3
x-a2a:
  verified: true
  probed: '2026-09-26'
  url: https://docs.afterquery.com/.well-known/agent-card.json
  grade: conformant
  protocol_version: '0.3'
  control: 404

AfterQuery API — frequently asked questions

Does AfterQuery have an API?

Yes. APIs.io lists 1 API from AfterQuery, including AfterQuery Experts Help Center MCP.

How do I authenticate with the AfterQuery API?

AfterQuery uses bearer-token authentication (1 scheme). The details are profiled on APIs.io as AfterQuery Authentication.

Does AfterQuery have an MCP server?

Yes. APIs.io lists 1 MCP server for AfterQuery: A read-only documentation MCP server over the AfterQuery Experts Help Center - full-text search across the help centre, a sandboxed read-only filesystem view of the documentation pages, and a feedback

Is the AfterQuery API ready for AI agents?

AfterQuery has a Kin Score of 24.4 out of 100 (emerging) and an Agent Readiness score of 21.2 (agent-aware), scored by API Evangelist on 2026-11-13.

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