Reality Defender

Reality Defender is an enterprise deepfake and AI-generated media detection platform that identifies manipulated images, video, audio, and text across calls, meetings, onboarding, and access workflows in real time. Its detection API accepts uploaded media or social-media URLs and returns an ensemble verdict aggregating multiple purpose-built detection models, letting platforms, financial institutions, and governments block deepfakes before they authorize payments, spread disinformation, or deceive AI agents. Reality Defender ships official SDKs for TypeScript, Python, Go, Rust, and Java, an open-source MCP server for agent integrations, and a Slack app. It was surfaced as a portfolio company of DCVC.

Reality Defender is listed with 1 API on the APIs.io network. Tagged areas include Company, Deepfake Detection, Artificial Intelligence, Media Authentication, and Content Moderation.

Reality Defender’s developer surface includes documentation, API reference, getting-started guide, support, engineering blog, signup flow, authentication, and 19 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

27.4/100 thin ▬ flat Agent 20/100 agent aware Front door AI 5/6 prominent Heartbeat 91/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

1 API 1 MCP Servers 1 Agent Skills

Company Deepfake Detection Artificial IntelligenceMedia AuthenticationContent Moderation Security Fraud PreventionSynthetic MediaMachine Learning

Kin Score

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

Composite quality — 27.4/100 · thin

Contract Quality 0.0 / 21

Developer Ergonomics 11.2 / 17

Access Clarity 4.7 / 17

Operational Transparency 0.3 / 11

Contract Governance 0.5 / 10

Discoverability 6.1 / 9

Regulatory Posture 3.3 / 15

Agent readiness — 20/100 · 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 8 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 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 6 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 6 / 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 AI & Biometrics 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
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
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)
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented)
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link

7 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 27.6 — up to +14.5 composite points
Operational Transparency scores 2.6 — up to +12.7 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/reality-defender/apis.yml: open an issue on github.com/api-evangelist/reality-defender 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
Biometrics Testing (biometric recognition vendors, identity verification depth)	builds-on	36.4	-	-
Zoom App Marketplace and Partner Ecosystem (builders and partners on Zoom)	builds-on	36.4	-	-

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.

Standards implemented 2

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.

Model Context Protocol (MCP)

measured — observed by APIs.io (documented)

Dynamic Client Registration

measured — observed by APIs.io (published)

APIs 1

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

Reality Defender Detection API

Asynchronous REST API for deepfake and manipulated-media detection. Request a pre-signed upload URL or submit a social-media URL, then poll for an ensemble detection verdict acr...

MCP Servers 1

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

Reality Defender MCP Server

MCP server; 3 tools listed.

MCP SERVER

Agent Skills 1

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

Detect a deepfake in a media file

AGENT SKILL

Security Posture 2

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

Reality Defender Authentication

apiKey/oauth2/openIdConnect · 2 schemes

SECURITY

Reality Defender Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 4

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Login

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

MCPServer

LLMsTxt

WellKnown

AgentSkill

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions

ErrorCatalog

Lifecycle

Conformance

DataModel

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 3

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

TrustCenter

TrustCenter

Authentication

Authentication

Operate 1

Status, limits, changes, and where to get help

Support

Support

Commercial 2

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

TermsOfService

TermsOfService

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: reality-defender
name: Reality Defender
description: Reality Defender is an enterprise deepfake and AI-generated media detection platform that identifies manipulated
  images, video, audio, and text across calls, meetings, onboarding, and access workflows in real time. Its detection API
  accepts uploaded media or social-media URLs and returns an ensemble verdict aggregating multiple purpose-built detection
  models, letting platforms, financial institutions, and governments block deepfakes before they authorize payments, spread
  disinformation, or deceive AI agents. Reality Defender ships official SDKs for TypeScript, Python, Go, Rust, and Java, an
  open-source MCP server for agent integrations, and a Slack app. It was surfaced as a portfolio company of DCVC.
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - security
  generated: '2026-11-06'
  method: derived
image: https://www.datocms-assets.com/157377/1744045826-og-image.jpg?auto=format&fit=max&w=1200
url: https://raw.githubusercontent.com/api-evangelist/reality-defender/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- dcvc
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
x-docs-platform: mintlify
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-10-04
x-docs-hosting: vercel
tags:
- Company
- Deepfake Detection
- Artificial Intelligence
- Media Authentication
- Content Moderation
- Security
- Fraud Prevention
- Synthetic Media
- Machine Learning
tags_raw:
- Company
- Deepfake Detection
- Artificial Intelligence
- Media Authentication
- Content Moderation
- Security
- Fraud Prevention
- Synthetic Media
- Machine Learning
- Machine-Learning
apis:
- name: Reality Defender Detection API
  description: Asynchronous REST API for deepfake and manipulated-media detection. Request a pre-signed upload URL or submit
    a social-media URL, then poll for an ensemble detection verdict across image, video, audio, and text inputs.
  humanURL: https://docs.realitydefender.com/api-reference/quickstart
  baseURL: https://api.prd.realitydefender.xyz
  tags:
  - Deepfake Detection
  - Media
  - Detection
  properties:
  - type: Documentation
    url: https://docs.realitydefender.com/api-reference/quickstart
  - type: Authentication
    url: authentication/reality-defender-authentication.yml
  - type: Conventions
    url: conventions/reality-defender-conventions.yml
  - type: ErrorCatalog
    url: errors/reality-defender-problem-types.yml
  - type: DataModel
    url: data-model/reality-defender-data-model.yml
  - type: Conformance
    url: conformance/reality-defender-conformance.yml
common:
- type: DomainSecurity
  url: security/reality-defender-domain-security.yml
- type: Website
  url: https://www.realitydefender.com
- type: DeveloperPortal
  url: https://docs.realitydefender.com/
- type: Documentation
  url: https://docs.realitydefender.com/
- type: APIReference
  url: https://docs.realitydefender.com/api-reference/quickstart
- type: GettingStarted
  url: https://docs.realitydefender.com/sdks/quickstart
- type: Support
  url: https://intercom.help/reality-defender/en/
- type: Blog
  url: https://www.realitydefender.com/blog
- type: GitHubOrganization
  url: https://github.com/Reality-Defender
- type: SignUp
  url: https://app.realitydefender.ai/
- type: Login
  url: https://auth.app.realitydefender.ai/
- type: PrivacyPolicy
  url: https://www.realitydefender.com/t-c/privacy-policy
- type: TermsOfService
  url: https://www.realitydefender.com/terms
- type: TrustCenter
  url: https://trust.realitydefender.com/
- type: Packages
  url: packages/reality-defender-packages.yml
- type: SDKs
  url: packages/reality-defender-packages.yml
- type: MCPServer
  url: mcp/reality-defender-mcp.yml
- type: LLMsTxt
  url: llms/reality-defender-llms.txt
- type: WellKnown
  url: well-known/reality-defender-well-known.yml
- type: Authentication
  url: authentication/reality-defender-authentication.yml
- type: Conventions
  url: conventions/reality-defender-conventions.yml
- type: ErrorCatalog
  url: errors/reality-defender-problem-types.yml
- type: Lifecycle
  url: lifecycle/reality-defender-lifecycle.yml
- type: Conformance
  url: conformance/reality-defender-conformance.yml
- type: DataModel
  url: data-model/reality-defender-data-model.yml
- type: AgentSkill
  url: skills/_index.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 13
  pass: local-v1

Reality Defender API — frequently asked questions

Does Reality Defender have an API?

Yes. APIs.io lists 1 API from Reality Defender, including Reality Defender Detection API.

How do I authenticate with the Reality Defender API?

Reality Defender documents its authentication (apiKey/oauth2/openIdConnect · 2 schemes). The details are profiled on APIs.io as Reality Defender Authentication.

Does Reality Defender have an MCP server?

Yes. APIs.io lists 1 MCP server for Reality Defender: MCP server; 3 tools listed.

Is the Reality Defender API ready for AI agents?

Reality Defender has a Kin Score of 27.4 out of 100 (thin) and an Agent Readiness score of 20.2 (agent-aware), scored by API Evangelist on 2026-11-06.

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