JsonCut
AI & AGENT BUILDERS

Give the agent
a visual production system.

Let agents create images and videos directly, build longer projects scene by scene and review real outputs before rendering.

MCP authoringScene patchesVisual review
WHAT THIS SOLVES

Give the agent structure.
Let it inspect the result.

JsonCut MCP gives AI builders focused tools for project authoring, media upload, template discovery, patching and visual review.

01

Avoid one giant payload

Long videos can be assembled and inspected incrementally as a persistent project.

02

Keep the schema approachable

Standard layers cover normal creative work while custom blocks provide a controlled escape hatch.

03

Review before publishing

Agents can inspect images and sampled frame grids, then patch only what needs correction.

PERSISTENT PROJECTS · VISUAL REVIEW

A clear path from
source to output.

Let agents create images and videos directly, build longer projects scene by scene and review real outputs before rendering.

  1. 01

    Create incrementally

    Build longer work in scenes and small project patches instead of one giant payload.

  2. 02

    Inspect real output

    Review the composed image or sampled video frames before publishing.

  3. 03

    Correct precisely

    Patch the affected layers or reuse an approved template for the next task.

USE IT FOR

Concrete work.
Not generic promises.

01Agent-created video
02AI content operations
03Template-driven agent workflows
RELEVANT EXAMPLES

See finished work.
Inspect the project behind it.

Show AI products, agents and automated workflows with motion-native diagrams, editable steps, variables and production-ready calls to action.

Explore ai & automation
CONTINUE THE WORKFLOW

The surrounding
pieces stay connected.

MCP for agentsMCP docsCustom blocks
CREATE · REVIEW · REUSE

Build the first result.
Keep the next one easier.

Start with a complete image or video project. Add templates, automation or an Agent where they remove repeated work.

Open JsonCut Studio