Skip to content

Rank #4 of 8 in Design & Prototyping

Penpot logo

Penpot

Open Source

Kaleidos Open Source S.L.

60k5.6k/yrnpm 3.2k/wk +324npm/wk +1k

Access

Install

dockercurl -o docker-compose.yaml https://raw.githubusercontent.com/penpot/penpot/main/docker/images/docker-compose.yaml && docker compose -p penpot -f docker-compose.yaml up -d
npmnpm install @penpot/plugin-types

Compare head-to-head

Alternatives to Penpot

Showcase

Penpot homepage screenshot
homepage · captured Sep 2026 · view live ↗
Penpot docs screenshot
docs · captured Sep 2026 · view live ↗

Try itExperimental

See what an agent can do with Penpot before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).

$docker compose up -d (official penpot docker-compose.yaml) # poll frontend :9001, then keyless MCP initialize against the bundled penpot-mcp servicerecorded session — replayed, not live
recorded 2026-09-07 · exit 0 · captured verbatim by our probe harness, secrets redacted

Verified integrations

Connections to other tracked products — hover a chip for the verbatim evidence quote behind it.

By theme — the product's score on each story themeBy theme

Agent design — stories about agent design in this arenaAgent designevidence →

Stories about agent design in this arena

34.3/100

Agenticness — how well agents can access and operate the productAgenticnessevidence →

How well agents can access and operate the product

35.3/100

Ai design — stories about ai design in this arenaAi designevidence →

Stories about ai design in this arena

20.0/100

Automation depth — how much of the product can run unattendedAutomation depthevidence →

How much of the product can run unattended

10.5/100

Collaboration multiplayer — stories about collaboration multiplayer in this arenaCollaboration multiplayerevidence →

Stories about collaboration multiplayer in this arena

12.0/100

Components design systems — stories about components design systems in this arenaComponents design systemsevidence →

Stories about components design systems in this arena

28.3/100

Dev handoff — stories about dev handoff in this arenaDev handoffevidence →

Stories about dev handoff in this arena

32.4/100

Openness — open source, data portability, and self-hosting storiesOpennessevidence →

Open source, data portability, and self-hosting stories

41.7/100

Plugins extensibility — stories about plugins extensibility in this arenaPlugins extensibilityevidence →

Stories about plugins extensibility in this arena

33.0/100

Pricing plans — plan structure and value — what each tier costs and what it unlocksPricing plansevidence →

Plan structure and value — what each tier costs and what it unlocks

24.0/100

Privacy posture — data-handling and privacy storiesPrivacy postureevidence →

Data-handling and privacy stories

32.9/100

Prototyping — stories about prototyping in this arenaPrototypingevidence →

Stories about prototyping in this arena

40.0/100

Vector editing — stories about vector editing in this arenaVector editingevidence →

Stories about vector editing in this arena

12.0/100

Versioning export — stories about versioning export in this arenaVersioning exportevidence →

Stories about versioning export in this arena

16.6/100

Story verdicts — every judged story with its evidenceStory verdicts

What’s free: 13 free · 0 paid · 0 enterprise · 26 not stated in evidence

?

Sorted by importance (agentic first) (high → low) · 53/53 stories · click a row’s chevron for the rationale and evidence

Connect an agent via an official MCP server G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full8/10T

Drive the product through a documented public API G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full8/10T

Plug MCP servers into this product so it can use their tools G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3partial3/10C

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness3none0/10

Point an agent at llms.txt or agent-oriented docs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Build against official SDKs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full7/10T

Operate the product with natural-language commands G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full7/10T

Subscribe to events via webhooks G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full7/10C

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial5/10C

Run the product headlessly / in CI for automation G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial5/10C

Set up automations that run autonomously in the background G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial4/10C

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Explore an interactive API reference with runnable examples G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Issue scoped/least-privilege API credentials for an agent G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Rely on versioned APIs with a documented deprecation policy G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Use an official CLI G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2noneuntestednone yet

Test against a sandbox environment without touching production data G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness1partial4/10C

Self-host the core product G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3fullfree8/10X

My coding agent can pull real design context — frames, variables, screenshots, component mappings — through an MCP server or API to implement the design C

Agent ops

ai-native userAgent design — stories about agent design in this arenaAgent design3partial6/10T

Prevent my data from being used to train AI models G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture3partialfree6/10C

Build reusable components with variants and per-instance overrides that stay linked to their source C

Design systems

designerComponents design systems — stories about components design systems in this arenaComponents design systems3partial5/10X

Export all of my data in open formats and leave G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3disputedfree5/10D

Inspect any layer and get measurements, styles, assets, and code snippets (CSS/iOS/Android) without an editor seat G

Handoff

developerDev handoff — stories about dev handoff in this arenaDev handoff3partialfree5/10C

My whole team can edit the same file simultaneously with live cursors and instant sync C

Collaboration

designerCollaboration multiplayer — stories about collaboration multiplayer in this arenaCollaboration multiplayer3disputed4/10D

Define rules that trigger actions automatically on events G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth3partial3/10C

I get professional vector tools — pen and path editing, boolean operations, precise alignment — for real interface design work C

Canvas

designerVector editing — stories about vector editing in this arenaVector editing3noneuntestednone yet

Choose where my data is stored (region/residency) G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2fullfree7/10C

An agent can create or modify designs programmatically — through a write-capable API, plugin surface, or MCP tools — not just read them C

Agent ops

ai-native userAgent design — stories about agent design in this arenaAgent design2partial6/10T

Designs map to production code — component-to-code mappings or direct design-to-code output I can actually ship C

Handoff

developerDev handoff — stories about dev handoff in this arenaDev handoff2partial6/10C

Extend the editor from a large plugin community or marketplace — icons, data fillers, accessibility checkers, and more G

Plugins

designerPlugins extensibility — stories about plugins extensibility in this arenaPlugins extensibility2partialfree6/10X

Read the product's source under an open license G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partialfree6/10C

Self-host the full design platform on my own infrastructure under an open-source license C

Files

developerVersioning export — stories about versioning export in this arenaVersioning export2disputedfree6/10D

The free tier supports real design work — usable editor and collaboration without a paid seat G

Pricing

designerPricing plans — plan structure and value — what each tier costs and what it unlocksPricing plans2partialfree6/10X

Wire screens into clickable prototypes with triggers, transitions, and overlays — no code required C

designerPrototyping — stories about prototyping in this arenaPrototyping2full6/10X

A documented plugin API with typings and samples lets me build and distribute my own editor extensions C

Plugins

developerPlugins extensibility — stories about plugins extensibility in this arenaPlugins extensibility2partial5/10C

An agent can render and export designs — screenshots, images, or production formats — through a documented programmatic surface C

Agent ops

ai-native userAgent design — stories about agent design in this arenaAgent design2partial5/10T

Do everything through the API that I can do in the UI G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partialfree5/10T

Frames can behave responsively — auto layout, constraints, and grids resize designs the way real UIs flex C

Canvas

designerVector editing — stories about vector editing in this arenaVector editing2partial5/10C

Generate or edit designs from a natural-language prompt — first drafts, layouts, or full mockups the tool actually produces C

Ai

designerAi design — stories about ai design in this arenaAi design2partialfree5/10T

Perform bulk operations across many items at once G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2disputed5/10D

Shared libraries publish components and styles across files and projects, with controlled updates when the source changes C

Design systems

designerComponents design systems — stories about components design systems in this arenaComponents design systems2partial5/10X

Control data retention and deletion G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partialfree4/10C

Manage design tokens or variables — colors, spacing, typography — with modes or themes applied across designs C

Design systems

designerComponents design systems — stories about components design systems in this arenaComponents design systems2partial4/10C

Comment directly on designs, mention teammates, and resolve threads so review happens in the file, not in email C

Collaboration

product managerCollaboration multiplayer — stories about collaboration multiplayer in this arenaCollaboration multiplayer2partial2/10C

Export production assets — PNG, SVG, PDF, and more — with per-layer presets, scales, and slices C

Files

designerVersioning export — stories about versioning export in this arenaVersioning export2none0/10

Opt out of telemetry and usage tracking G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2nonefree0/10

Schedule recurring jobs or workflows G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2none0/10

Full version history lets me name milestones, compare, and restore any earlier state of a file C

Files

designerVersioning export — stories about versioning export in this arenaVersioning export2noneuntestednone yet

The file format is open or documented, so my designs stay portable and toolable outside the vendor's editor C

Files

developerVersioning export — stories about versioning export in this arenaVersioning export1full8/10C

Built-in AI handles asset chores — image generation, background removal, content-aware fills, copy suggestions — inside the editor C

Ai

designerAi design — stories about ai design in this arenaAi design1none0/10

Prototypes can carry advanced behavior — animation between states, conditions or variables, scroll effects — to feel like the real product C

designerPrototyping — stories about prototyping in this arenaPrototyping1none0/10

Published plan pricing makes seat types, tiers, and AI-feature gating clear before procurement G

Pricing

product managerPricing plans — plan structure and value — what each tier costs and what it unlocksPricing plans1none0/10

Version, review, and roll back my automations G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth1noneuntestednone yet

Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 39 stories with headroom

What would move Penpot’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.

  1. Agenticness — how well agents can access and operate the productDelegate tasks to a built-in AI assistant inside the product

    nonemoves Built-in AIimpact 45

    Penpot's AI evidence is entirely about an MCP server that lets external AI agents/LLMs connect to Penpot's data (penpot-docs-1, penpot-docs-18, penpot-docs-27, penpot-docs-31, penpot-docs-39), not about a built-in AI assistant embedded in the product itself that users can delegate tasks to.

  2. Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools

    partialq3/10moves agent-readyimpact 31.5

    Missing: documentation of a general-purpose MCP client/connector UI in Penpot, a list of supported external MCP servers beyond Figma, and any hands-on/community confirmation that this client-side integration works.

  3. Vector editing — stories about vector editing in this arenaI get professional vector tools — pen and path editing, boolean operations, precise alignment — for real interface design work

    nonemoves PA Scoreimpact 30

    The evidence pack covers AI/MCP integration, self-hosting, plugins, components, prototyping, and design tokens, but contains no documentation or hands-on mention of pen/path editing tools, boolean path operations, or precise alignment/snapping features.

  4. Agenticness — how well agents can access and operate the productUse an official CLI

    nonemoves agent-readyimpact 30

    Evidence covers Penpot's MCP server, plugin API, webhooks, and REST access tokens, but there is no mention of an official CLI tool for interacting with Penpot as an AI-native workflow interface.

  5. Agenticness — how well agents can access and operate the productIssue scoped/least-privilege API credentials for an agent

    nonemoves agent-readyimpact 30

    Missing: scoped/permission-limited token creation, documentation of least-privilege API key options, agent-specific credential management.

  6. Agenticness — how well agents can access and operate the productExplore an interactive API reference with runnable examples

    nonemoves API qualityimpact 30

    Evidence describes integrations-api, plugin system, and MCP server, but there is no interactive API reference with runnable examples; probes explicitly found no OpenAPI/swagger spec or llms.txt documentation endpoint (404s), and no mention of interactive docs/sandbox exists.

  7. Agenticness — how well agents can access and operate the productDownload a machine-readable API spec (OpenAPI or equivalent)

    nonemoves API qualityimpact 30

    While Penpot documents a general integrations API, access tokens, webhooks, and an MCP server, there is no evidence of a downloadable OpenAPI/Swagger spec; direct probes for openapi.json/swagger.json/llms.txt all returned 404s, indicating no machine-readable API spec is published.

  8. Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy

    nonemoves API qualityimpact 30

    Missing: any documented API version scheme, deprecation notices, or changelog governing breaking changes.

Showing the top 8 of 39 — every none/partial verdict in the story verdicts table is headroom.

Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.

Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map13 surfaces · 38 covered stories

Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.

Probe proofs — replayable recordings from the probe harnessProbe proofs

Replayable recordings from our probe harness — see the Prove-It protocol to submit one.

$docker compose up -d (official penpot docker-compose.yaml) # poll frontend :9001, then keyless MCP initialize against the bundled penpot-mcp servicereproduced
$ docker compose up -d (official penpot docker-compose.yaml) # poll frontend :9001, then [redacted]less MCP initialize against the bundled penpot-mcp service
<title>Penpot | Full-stack design</title>
event: message
data: {"result":{"protocolVersion":"2025-06-18","capabilities":{"tools":{"listChanged":true}},"serverInfo":{"name":"penpot","version":"1.0.0"},"instructions":"You have access to Penpot tools in order to interact with Penpot designs.\nBefore working with these tools, be sure to read the 'Penpot High-Level Overview' via the `high_level_overview` tool.\n"},"jsonrpc":"2.0","id":1}

Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence

7 of 17 testable claims verified · 2 contradictedintegrity 18/100

25 distinct capability claims found in Penpot’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.

7

Verified

8

Unverified

2

Contradicted

19

Undersold

Verified (11)
Unverified (9)
Contradicted (3)
Undersold (19)
Claims outside our story set (6)

Real capability claims found in Penpot’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.

  • Automates tedious tasks and streamlines workflows between design and code apps via AI agents

    source ↗
  • Supports unlimited teams collaborating freely

    source ↗
  • No limit on number of files, only limited by storage capacity

    source ↗
  • Designs can be migrated from Figma into Penpot by connecting each tool's MCP

    source ↗
  • A deleted main component can be restored from an existing linked copy

    source ↗
  • A Penpot instance can be set up in about 3 minutes

    source ↗
Suggest a story for these →

Business model

open-sourcefree-tiersubscription-per-seatenterprise-custom

MPL-2.0 open source and free to self-host (official docker compose incl. a first-party MCP service); hosted SaaS has a free tier plus per-seat Unlimited/Enterprise plans and a private-server offering.

pricing ↗

Score trend

How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.

PA Score37 (Sep 7 '26)30 (Sep 16 '26)
Agent-ready50 (Sep 7 '26)49 (Sep 16 '26)

Try Experimental

Run it in the microterminal →

Recorded agent sessions — and a live MCP handshake where the vendor ships one.

Flag

⚑ Flag a verdict

Think a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.

Badge

Embed this product's score badge →

Hotlinked SVG — always shows the live current score.

For agents

Data