Flato.ai

Flato gives AI agents and human editors an editable canvas to continuously create, refine, animate, and export presentations from rough draft to ready-to-present. It offers a native canvas runtime for AI design, supporting multi-format output, cross‑modal design, and programmable AI design workflows, enabling both agents and users to collaborate on AI‑generated presentations.

Flato.ai is listed with 1 API on the APIs.io network. Tagged areas include Artificial Intelligence, Presentation, Canvas, Design, and MCP.

Flato.ai’s developer surface includes documentation, API reference, pricing, engineering blog, getting-started guide, and 9 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

22.7/100 emerging Agent 18/100 agent aware Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

AccessFreemium

1 API

Artificial Intelligence Presentation Canvas Design MCP

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 22.7/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 5.3 / 17

Access Clarity 8.7 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.0 / 10

Discoverability 5.6 / 9

Regulatory Posture 1.9 / 15

Agent readiness — 18/100 · 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 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 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 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.

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 Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0 Ask about this →
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented) Ask about this →

9 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 Ask about this →
Developer Ergonomics scores 31.0 — up to +13.8 composite points Ask about this →
Operational Transparency scores 0.0 — up to +13.0 composite points Ask about this →

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.

Not sure how this applies to your stack? Ask about any one item. Kin Lane reads every question, looks at your profile and your situation, and replies with what a fix would take — scoped to that one area, priced up front, yours whether you ship it or not. Ask a question →

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/flato-ai/apis.yml: open an issue on github.com/api-evangelist/flato-ai 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 →

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.

Flato MCP

Flato MCP provides an API for AI agents to create, inspect, and update editable Flato canvas projects.

Flato.ai API pricing

Prices published by Flato.ai, read 2026-11-08 from www.flato.ai/docs/pricing.

Plan	Price
Free	$0
Basic (Yearly)	$100
Basic (Monthly)	$10
Basic (Single-month purchase)	$18
Plus (Yearly)	$270
Plus (Monthly)	$27
Plus (Single-month purchase)	$49

Plan details, limits and sources →

Pricing Plans 1

Published pricing tiers and plan structures.

Flato.ai Plans Pricing

7 plans

PLANS

Security Posture 1

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

Flato.ai Domain Security

TLSv1.3

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

WellKnown

WellKnown

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Commercial 4

Pricing, plans, and the legal terms of use

Plans

Pricing

TermsOfService

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 2

Properties that don't map to a standard resource type

Hosts

Hosts

Vendors

Vendors

Source (apis.yml)

aid: flato-ai
name: Flato.ai
description: Flato gives AI agents and human editors an editable canvas to continuously create, refine, animate, and export
  presentations from rough draft to ready-to-present. It offers a native canvas runtime for AI design, supporting multi-format
  output, cross‑modal design, and programmable AI design workflows, enabling both agents and users to collaborate on AI‑generated
  presentations.
url: https://artifacts.apis.io/flato-ai/apis.yml
x-type: company
x-source: harvest:mcp-registry
x-tier: profiled
x-tier-reason: enrichment pass 2026-11-08 (modular-v1; was harvest)
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-13'
  method: derived
specificationVersion: '0.20'
created: '2026-11-08'
modified: '2026-11-08'
tags:
- Artificial Intelligence
- Presentation
- Canvas
- Design
- MCP
tags_raw:
- AI
- Presentation
- Canvas
- Design
- MCP
image: https://www.flato.ai/assets/flato_logo/flato_logo_white.svg
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Plans
  url: plans/flato-ai-plans-pricing.yml
- type: LLMsTxt
  url: llms/flato-ai-llms.txt
- type: WellKnown
  url: well-known/flato-ai-well-known.yml
- type: Hosts
  url: hosts/flato-ai-hosts.yml
- type: Vendors
  url: vendors/flato-ai-vendors.yml
- type: DomainSecurity
  url: security/flato-ai-domain-security.yml
- type: Website
  url: https://flato.ai/
- type: Documentation
  url: https://www.flato.ai/docs/how-flato-works
- type: APIReference
  url: https://www.flato.ai/docs/mcp
- type: Pricing
  url: https://www.flato.ai/price
- type: TermsOfService
  url: https://www.flato.ai/docs/terms-of-use
- type: PrivacyPolicy
  url: https://www.flato.ai/docs/privacy-policy
- type: Blog
  url: https://www.flato.ai/blogs
- type: GettingStarted
  url: https://www.flato.ai/docs/mcp#quickstart
apis:
- name: Flato MCP
  description: Flato MCP provides an API for AI agents to create, inspect, and update editable Flato canvas projects.
  humanURL: https://www.flato.ai/docs/mcp
  baseURL: https://api.flato.ai/api/mcp
  aid: flato-ai:flato-mcp
x-enrichment:
  date: '2026-11-08'
  status: enriched
  artifacts_added: 11
  pass: modular-v1
  engine: identity=local,contract=local,surfaces=local,docs=local,regulatory=local

Flato.ai API — frequently asked questions

Does Flato.ai have an API?

Yes. APIs.io lists 1 API from Flato.ai, including Flato MCP.

How much does the Flato.ai API cost?

Flato.ai publishes its prices; its Free plan is $0 as of 2026-11-08. APIs.io lists 7 pricing plans for Flato.ai, with each plan's price, limits and inclusions under Pricing on this page.

Is the Flato.ai API ready for AI agents?

Flato.ai has a Kin Score of 22.7 out of 100 (emerging) and an Agent Readiness score of 18.2 (agent-aware), scored by API Evangelist on 2026-11-13.

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get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
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apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
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