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AWS Labs Nova Canvas vs Mocapless

AWS Labs Nova Canvas is an MCP server published by awslabs. Marketplaces we read that list it: 1 (Docker MCP Catalog). Mocapless is an MCP server published by halifa-bar. Marketplaces we read that list it: 1 (Official MCP Registry). As of our marketplace pass on 2026-10-21. This pair was picked by a reader, not by our comparison rule, so search engines are asked not to index the page.

Where each is published

Where each is published
MarketplaceAWS Labs Nova CanvasMocapless
Docker MCP Catalog Listed
Version: sha256:5582496accaa
Forks (GitHub): 1 820
Pulls (Docker Hub): 11 206
Stars (Docker Hub): 0
Stars (GitHub): 9 803
Not marked · First seen
Not listed
Official MCP Registry Not listed Listed
Version: 0.2.0
No figure published
Not marked · First seen

Each figure is the marketplace's own and is never added up across marketplaces. A marketplace that publishes no figure shows none: no number is not zero.

The facts side by side

AWS Labs Nova Canvas vs Mocapless
FactAWS Labs Nova CanvasMocapless
Marketplaces that list it11
Stars (GitHub) (differs)9 803No figure on GitHub
Pulls (Docker Hub) (differs)11 206No figure on Docker Hub
Forks (GitHub) (differs)1 820No figure on GitHub
Last releaseNot publishedNot published
Where it runs (differs)On your machine (mcp/nova-canvas-mcp-server)Remote server (api.mocapless.com/mcp)
Transport (differs)stdioStreamable HTTP
Tools it declares (differs)2Not published
Environment variables it asks for (differs)5, secrets among them: 21, secrets among them: 1
Licence (differs)Apache-2.0Not stated
Repository (differs)github.com/awslabs/mcpNot stated
Changes in the last 7 days (differs)02
First seen (differs)2026-10-112026-10-17
Endpoint at the last check (differs)no remote endpoint we checknot checked yet

Lines where the two differ have a tinted background and bold values. Where the data itself says which value is better (more marketplaces, a larger figure of the same marketplace, a fresher release, a verified mark on a marketplace that lists both), the better one is also marked green with ▲ and the worse one red with ▼. Where it runs, the transport, the tools, the settings, hooks, the bundle's parts, the licence and the week's changes are marked only as different: more or fewer is not better in itself.

What each says it does

AWS Labs Nova Canvas

In its own words, on Docker MCP Catalog:

AI image generation using Amazon Nova Canvas.

Mocapless

In its own words, on Official MCP Registry:

Rig and animate 3D animals and characters from a sentence. Get FBX and GLB for any engine.

How to run each

AWS Labs Nova Canvas As a local MCP server: Docker image

Claude Code
claude mcp add --env "AWS_SECRET_ACCESS_KEY=<YOUR_AWS_SECRET_ACCESS_KEY>" --env "AWS_SESSION_TOKEN=<YOUR_AWS_SESSION_TOKEN>" --transport stdio awslabs-nova-canvas -- docker run -i --rm -e AWS_SECRET_ACCESS_KEY -e AWS_SESSION_TOKEN mcp/nova-canvas-mcp-server

Requires: AWS_SECRET_ACCESS_KEY (secret), AWS_SESSION_TOKEN (secret)

Mocapless As a remote MCP server

Claude Code
claude mcp add --transport http mocapless https://api.mocapless.com/mcp

Requires: MOCAPLESS_API_KEY (secret)

Commands built only from what the marketplaces declare; the full set for every client is on each card.

Tools each declares

The marketplaces of Mocapless publish no list of tools, so we do not compare tools.

Settings each asks for

Only AWS Labs Nova Canvas asks for

  • AWS_ACCESS_KEY_ID
  • AWS_PROFILE
  • AWS_REGION
  • AWS_SECRET_ACCESS_KEY (secret)
  • AWS_SESSION_TOKEN (secret)

Only Mocapless asks for

  • MOCAPLESS_API_KEY (secret)

Settings as each marketplace publishes them. Asking for fewer is not better in itself.

What it can do: AWS Labs Nova Canvas · What it can do: Mocapless · Compare two other plugins

Data comes from the Docker MCP Catalog (desktop.docker.com/mcp/catalog) and Docker Hub. Data comes from the Official MCP Registry (registry.modelcontextprotocol.io), CC0 1.0. Figures come from our own regular passes over the marketplaces, last read on . We publish no contact details for plugin publishers.

Where the data comes from: how the catalog is built