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hayhihey

Google AI Edge Gallery Video MCP Server

by hayhihey

edge_video_create

Converts a text prompt into a styled MP4 video with storyboards, Ken Burns motion, color grading, and optional soundtrack, then exports it to Android Gallery or Google Photos.

Instructions

End-to-end prompt-to-video pipeline powered by Google AI Edge Gallery standards. Plans storyboard scenes, renders keyframes, applies Ken Burns motion and color grading, compiles into MP4, and syncs directly to Android DCIM Gallery / Google Photos.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoAesthetic style and motion dynamicssocial_reel
titleNoOptional custom title for the video
promptYesThe video concept, prompt, or script
aspectRatioNoAspect ratio: 9:16 (vertical reel/short), 16:9 (landscape), 1:1 (square)9:16
applyMotionFxNoApply dynamic Ken Burns camera motion (pan/zoom)
addBackgroundScoreNoSynthesize ambient Edge AI background soundtrack
targetDurationSecondsNoTotal video length in seconds (3 - 120s)
exportToAndroidGalleryNoExport and index into Android MediaStore / Google Photos

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It does disclose real side effects beyond the schema - writing output to Android DCIM Gallery / Google Photos and indexing into MediaStore - which is genuinely useful. However, it omits runtime/latency expectations, permissions or environment requirements, whether existing files are overwritten, and any failure/re-run behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence, front-loaded with what the tool is, followed by the pipeline stages in execution order - it is dense and every clause carries information. Minor waste in the branding phrase 'powered by Google AI Edge Gallery standards', which does not help an agent act.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter, multi-stage generation tool with no output schema, the description covers the workflow and destination well but never says what the call returns (file path, URI, job id, or whether it is synchronous). An agent cannot tell how to retrieve or verify the resulting video, and there is no output schema to compensate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter (style, aspectRatio, targetDurationSeconds range, motion/score/gallery toggles) is already documented in the schema with defaults and enums. The description adds no parameter-level syntax, constraints, or interactions, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource ('prompt-to-video pipeline') and enumerates the concrete stages it performs (storyboard, keyframes, motion/grading, MP4 compile, gallery sync). This implicitly distinguishes it from the step-level siblings (edge_storyboard_plan, edge_generate_keyframes, edge_apply_video_fx, edge_compile_video), but it never names them or explicitly frames itself as the orchestrating shortcut.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the phrase 'End-to-end ... pipeline' signals this is the all-in-one path versus the granular sibling tools, but there is no explicit when-to-use, when-not-to-use, or alternative-naming guidance. An agent must infer the routing decision rather than read it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.