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Ai Video Style Transfer

AI-Video-Style-Transfer

Create unique videos with our AI Video Filters and Effects. Easily enhance each video with stunning AI styles. AI Video Filters with Instant Transformation. Experience a seamless transformation with AI video filters that apply stunning effects instantly. Choose from an array of unique styles, including pop art, retro, anime, and more, to add depth and creativity to every frame. Sample usage cases:

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pollingNoIf true (default), keep polling until the task finishes, returning the final result. If false, return immediately without waiting for the task to finish.
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.3/5.0
Behavior2/5

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

Beyond the annotations (readOnlyHint=false, etc.), the description adds little. It claims 'instant transformation' which is vague and possibly misleading given the polling parameter implies an asynchronous workflow. It doesn't mention the need for a template_id, file URL, or any behavioral constraints.

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

Conciseness2/5

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

The description is repetitive ('AI Video Filters with Instant Transformation' and 'apply stunning effects instantly') and contains marketing fluff. It ends abruptly with 'Sample usage cases:' without actual examples, making it feel unfinished.

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

Completeness2/5

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

The tool is complex with required parameters like template_id, dst_duration, and source file, but the description doesn't explain the workflow (e.g., need to list templates first) or mention output/error behavior. It relies entirely on the schema, which is incomplete for the top-level request object.

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

Parameters2/5

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

Schema description coverage is only 50% as the 'request' parameter lacks a top-level description. The description mentions 'styles' but doesn't explain how template_id, dst_duration, or src_file_url/id are used. It does not compensate for the schema gap.

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

Purpose3/5

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

The description says it enhances videos with AI styles and applies effects, which indicates style transfer, but it uses broad marketing language like 'Create unique videos' and 'AI Video Filters' rather than explicitly stating 'style transfer' or the template-based mechanism. It doesn't clearly distinguish from sibling AI-Video-Enhancer.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites like listing templates or uploading files, and ends with 'Sample usage cases:' but provides none.

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

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TDQS

C2.4/5.0
Disambiguation3/5

Many tools are clearly distinct (e.g., AI-Object-Removal-Pro vs AI-Replace), but there is notable overlap among upload-related tools (File-Upload, Get-Upload-API-Info, upload_file) and among photo enhancement tools (Enhance, Color-Correction, Lighting) that could cause misselection. Template-listing tools are repetitive but each is tied to a specific generator.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use PascalCase with dashes (AI-Avatar-Generator), some use verb-first patterns (Get-Feature-Cost, Get-Running-Task-Status), and one uses lowercase snake_case (upload_file). The AI- prefix is consistent for many tools, but the overall pattern is mixed.

Tool Count2/5

With 34 tools, the server feels overloaded. Many tools are variants of similar operations (e.g., numerous template listing tools) and could be consolidated or eliminated. The count exceeds the 25+ threshold for 'too many'.

Completeness4/5

The tool surface covers a broad range of AI media editing operations: photo and video generation, enhancement, background editing, face swap, object removal, and upload/status management. Minor gaps like video background removal (only replacement available) exist, but core workflows are well-supported.

Resources