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Ai Image Generator Text To Image

AI-Image-Generator-Text-to-Image

Discover the power of AI with our innovative text-to-image generator! Transform your ideas into stunning visuals instantly, experiment with prompts, explore unique styles like cartoons, oil paintings, or sketches, and let your creativity shine through. Whether you're an artist, designer, or creative soul, our tool offers endless possibilities to bring your vision to life. Add images as references to inspire new artistic directions while letting AI refine them into entirely original masterpieces. Want more inspirations? Please refer to Use cases: Sample output:

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

D1.8/5.0
Behavior2/5

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

Annotations indicate a non-read-only, non-idempotent operation, but the description adds no behavioral context such as polling behavior, cost, or output format. The sentence 'let AI refine them into entirely original masterpieces' is vague and not informative about how the tool operates.

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

Conciseness1/5

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

The description is verbose and promotional, with fragmented sections like 'Want more inspirations? Please refer to', 'Use cases:', and 'Sample output:' that are left empty. It is not front-loaded and contains no concrete technical information, making it largely filler.

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

Completeness1/5

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

Despite having a nested request object, a polling parameter, and an output schema, the description fails to explain the asynchronous behavior, return values, or how to construct a valid request. The incomplete 'Use cases' and 'Sample output' sections leave the agent without essential context.

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?

The description does not mention any of the parameters (polling, request, prompt, size, etc.) and fails to compensate for the 50% schema coverage. The schema itself provides some descriptions, but the description contributes zero parameter semantics.

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

Purpose2/5

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

The description uses marketing language like 'text-to-image generator' and 'transform your ideas into stunning visuals' rather than a clear verb+resource statement. It also mentions 'Add images as references,' which is not supported by the input schema and blurs the boundary with the sibling tool AI-Image-Generator-Image-to-Image.

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?

There is no guidance on when to use this tool over alternatives. The description mentions generic creative audiences but provides no explicit when-to-use or when-not-to-use scenarios, nor does it reference any of the many sibling image/video generation tools.

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