Need help with your APIs? I offer API discovery, governance & evangelism services. Explore services →
API Evangelist API Evangelist
Discovery
Learnings
Guidance
Toolbox
Alignment
API Evangelist LLC
Karat website screenshot

Karat

Karat Inc. is a Seattle-based technical interviewing platform that conducts standardized software engineering interviews for enterprise hiring teams through its community of trained Interview Engineers. Karat exposes a GraphQL API, hosted per-customer at https://{subdomain}.karat.io/api/v1/graphql, that lets talent and ATS systems programmatically manage roles and groups, look up users, invite candidates into assessments, retrieve candidacy statuses, code-challenge and interview results, and bulk-update candidacy dispositions. The API uses Bearer token authentication, Relay-style cursor pagination, and ships an example Python SDK and a Postman collection. Karat is SOC 2 Type II certified and certified under the EU-US, UK-US and Swiss-US Data Privacy Frameworks.

agent aware

Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.

Kin Score

API Evangelist profiles Karat the way a machine reads it — 5 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Karat scores 32.5/100 (thin), with a separate agent-readiness read of 30/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 32.5/100 · thin
Contract Quality 0.0 / 25
Developer Ergonomics 15.2 / 20
Commercial Clarity 7.4 / 20
Operational Transparency 0.7 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 30/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
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 0 / 7
Typed Event Surface 0 / 6
Agent Skills 5 / 5
Well-Known Catalog 4 / 4
Consent & Bot Identity 0 / 3

How we profile Karat

Each block below is one kind of artifact we hold for Karat. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

APIs 1

Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.

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

Karat GraphQL API

Karat's GraphQL API for managing technical-interview hiring workflows: query candidacies, roles, groups and users; invite candidates into assessments; and bulk-update candidacy ...

MCP Servers 1

Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.

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

karat-mcp.yml

MCP SERVER

Security Posture 3

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

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

Karat Authentication

http · 1 scheme

SECURITY

Karat Domain Security

TLSv1.3 · DMARC

SECURITY

Karat Trust Center

SOC 2 Type II, EU-US Data Privacy Framework, UK-US Data Privacy Framework, Swiss-US Data Privacy Framework

SECURITY

Resources

Every other property we hold for Karat — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Get Started 2

Portal, sign-up, and the first successful call

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Build 4

SDKs, sample code, and the tooling you integrate with

Operate 1

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/karat · machine-readable index on apis.io