Arpeggi Labs
Arpeggi Labs is the company behind Kits AI, a studio-quality AI music and audio platform for musicians, producers, and developers. Kits AI provides voice cloning and conversion, an AI singing generator with 100+ royalty-free artist voice models, vocal isolation, stem separation, AI mastering, and a voice-model blender, alongside an ethically sourced "Earn" program that pays vocalists to license digital clones of their voice. The Kits AI API exposes these capabilities as asynchronous inference jobs over a REST interface at arpeggi.io/api/kits/v1, authenticated with a bearer API key: create a voice conversion, vocal separation, stem split, or voice-blend job, then poll for the signed output file URLs. Arpeggi Labs is an a16z portfolio company; its earlier product was Arpeggi Studio, a web3 in-browser music creation platform.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles Arpeggi Labs the way a machine reads it — 9 machine-readable artifacts across 5 APIs, 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 — Arpeggi Labs scores 50.4/100 (developing), with a separate agent-readiness read of 58/100 (agent ready). 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 Arpeggi Labs
Each block below is one kind of artifact we hold for Arpeggi Labs. 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 5
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.
Arpeggi Labs Stem Splitter API
Split an audio track into vocal and instrument stems.
Arpeggi Labs Vocal Separation API
Isolate vocals from a mixed audio track.
Arpeggi Labs Voice Blender API
Blend two to four voice models into a new voice model.
Arpeggi Labs Voice Conversion API
Convert an input performance to a target voice model.
Arpeggi Labs Voice Models API
Browse and retrieve available voice models.
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.
arpeggi-labs-mcp.yml
MCP SERVERRate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Arpeggi Labs Rate Limits
RATE LIMITSSecurity 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 Arpeggi Labs — 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 3
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 3
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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