Magic
Magic (magic.dev) is a San Francisco frontier AI research lab building frontier-scale code models - an "AI coworker" for software engineering, and ultimately a path to safe AGI - rather than a shipping developer product. It has raised roughly $515M from Nat Friedman, Daniel Gross, CapitalG, Elad Gil, Sequoia, Jane Street, and Eric Schmidt, and has published research on ultra-long-context models (LTM-1 at a 5M token context window, and the unreleased LTM-2-mini research prototype claimed to handle up to 100M tokens). As of this review Magic does not publish a public, self-serve developer API, API reference, SDK, or waitlist; its website and careers pages describe mission, research, and open roles only, with no product access model, pricing, or documented endpoints. Its GitHub organization (magicproduct) hosts research tooling (e.g. hash-hop, a long-context evaluation harness) and infrastructure forks, not an API client or SDK.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles Magic the way a machine reads it — 2 machine-readable artifacts, 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 — Magic scores 7.9/100 (minimal), with a separate agent-readiness read of 0/100 (human only). 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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Magic
Each block below is one kind of artifact we hold for Magic. 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.
Security Posture 2
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.
Resources
Every other property we hold for Magic — 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.
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Company 4
The organization behind the API
Other 1
Properties that don't map to a standard resource type
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