Silk Labs

Silk Labs was an on-device artificial intelligence startup founded in 2015 by former Mozilla CTO Andreas Gal together with Chris Jones and Michael Vines, a team drawn from Mozilla's Firefox OS effort. The company's open-source Silk platform layered a Node.js runtime on Android so developers could build Internet of Things applications entirely in JavaScript, and it later shipped work on the "Sense" AI home camera focused on running real-time visual and audio recognition directly on the device. Silk Labs was backed by investors including 500 Global and was acquired by Apple in November 2018, after which it ceased independent operations; the silklabs.com domain is now parked on Apple nameservers. Its open-source Silk code, GitHub organization, and npm packages remain publicly available and are captured in this profile.

Silk Labs is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine Learning, IoT, and On-Device AI.

Silk Labs’ developer surface includes documentation, CLI, and 11 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

12.1/100 emerging ▬ flat Agent 0/100 human only Heartbeat 0/100 dormant self hosted · MIT Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs

Company Artificial Intelligence Machine Learning IoT On-Device AI JavaScript Open Source SDK Computer Vision

Kin Score

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

Composite quality — 12.1/100 · emerging

Contract Quality 0.0 / 19

Developer Ergonomics 3.6 / 15

Access Clarity 0.0 / 15

Operational Transparency 0.3 / 10

Contract Governance 0.0 / 9

Discoverability 4.2 / 8

Regulatory Posture 0.8 / 15

Open Source Surface 4.0 / 10

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 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.

Open Source Surface applies to this provider. This product is open source and we read its repository directly, so Open Source Surface carries 10 points of the composite. It is scored from what the repository actually publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the provider rather than inferred from our own catalog pointers. This facet adds; nothing was taken away to make room for it. An open-source project is not excused from the commercial facets, because exemption would strip it of the points it does earn. If we have the wrong repository, or this product is not open source, say so on your provider repo and we will drop the facet rather than have you publish against 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 75 points between them, because both conditional facets apply and carry 25 points together. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% 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
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
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

13 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
Access Clarity scores 0.0 — up to +20.0 composite points
Developer Ergonomics scores 23.8 — up to +15.2 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/silk-labs/apis.yml: open an issue on github.com/api-evangelist/silk-labs 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 →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
ONVIF Video Analytics (video surveillance, edge cameras, computer vision)	distribution	9.6 (thin)	-	1

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Security Posture 1

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

Silk Labs Domain Security

no transport/DNS hardening detected

SECURITY

Resources

Documentation 2

Reference material describing how the API behaves

ContributionGuide

ContributionGuide

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Build 6

SDKs, sample code, and the tooling you integrate with

CodeOfConduct

CodeOfConduct

GitHubOrganization

SourceCode

Packages

SDKs

CLI

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

IssueTracker

IssueTracker

Commercial 1

Pricing, plans, and the legal terms of use

License

License

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: silk-labs
deliveryModel:
  model: self-hosted
  license: MIT
  open_source: true
  commercial: false
  callable_host: false
  label: Self-hosted open source · you run it yourself
  confidence: high
  source:
  - license
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/silk-labs.png
name: Silk Labs
description: Silk Labs was an on-device artificial intelligence startup founded in 2015 by former Mozilla CTO Andreas Gal
  together with Chris Jones and Michael Vines, a team drawn from Mozilla's Firefox OS effort. The company's open-source Silk
  platform layered a Node.js runtime on Android so developers could build Internet of Things applications entirely in JavaScript,
  and it later shipped work on the "Sense" AI home camera focused on running real-time visual and audio recognition directly
  on the device. Silk Labs was backed by investors including 500 Global and was acquired by Apple in November 2018, after
  which it ceased independent operations; the silklabs.com domain is now parked on Apple nameservers. Its open-source Silk
  code, GitHub organization, and npm packages remain publicly available and are captured in this profile.
url: https://raw.githubusercontent.com/api-evangelist/silk-labs/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- 500-global
x-tier: stub
x-tier-reason: portfolio-lead
x-status: acquired
x-acquired-by: Apple
x-acquired-date: '2018-11-22'
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Artificial Intelligence
- Machine Learning
- IoT
- On-Device AI
- JavaScript
- Open Source
- SDK
- Computer Vision
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Internet of Things
- On-Device AI
- JavaScript
- Open Source
- SDK
- Computer Vision
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: IssueTracker
  url: https://github.com/silklabs/silk/issues
- type: CodeOfConduct
  url: https://github.com/silklabs/silk/blob/master/docs/code-of-conduct.md
- type: ContributionGuide
  url: https://github.com/silklabs/silk/blob/master/CONTRIBUTING.md
- type: License
  name: MIT
  url: https://github.com/silklabs/silk/blob/master/LICENSE
- type: Website
  url: https://silklabs.com
- type: GitHubOrganization
  url: https://github.com/silklabs
- type: SourceCode
  url: https://github.com/silklabs/silk
- type: Documentation
  url: https://github.com/silklabs/silk/tree/master/docs/tutorial
- type: Packages
  url: packages/silk-labs-packages.yml
- type: SDKs
  url: packages/silk-labs-packages.yml
- type: CLI
  url: cli/silk-labs-cli.yml
- type: LLMsTxt
  url: llms/silk-labs-llms.txt
- type: DomainSecurity
  url: security/silk-labs-domain-security.yml
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 4
  pass: local-v1
x-lifecycle:
  state: deprecated
  reason: domain-does-not-resolve
  observed: '2026-09-27'
  detail: The company's own domain returned no A or AAAA record when probed. This is an observation about the domain, not
    a request from the company.
  indexed: true
  successor: Apple
  successor_in_catalog: true

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