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ex-takashima

OpenAI GPT-Image MCP Server

by ex-takashima

get_metadata_from_image

Extract embedded metadata from generated PNG/JPEG images to retrieve UUID, parameter hash, generation settings, and verify database integrity.

Instructions

Extract and display embedded metadata from a generated image file. Shows UUID, parameter hash, generation settings, and verifies integrity with database. Works with PNG and JPEG images that contain embedded OpenAI GPT-Image metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_pathYesPath to the image file to read metadata from
Behavior4/5

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

With no annotations, the description discloses key behaviors: it shows specific metadata fields and verifies integrity with a database. It implies read-only operation by using 'extract and display' and specifies file format support.

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

Conciseness5/5

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

The description is only two sentences, front-loaded with the core action, and every sentence contributes essential information without redundancy or fluff.

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

Completeness4/5

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

Given the tool's low complexity (single parameter, no output schema), the description adequately covers what the tool does, what it returns, and applicable file types. It could mention error cases but is still sufficient for correct use.

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

Parameters4/5

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

The single parameter 'image_path' is fully described in the schema (100% coverage). The description adds context by specifying that the path should point to a generated image with OpenAI metadata, which enriches the schema description.

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

Purpose5/5

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

The description clearly states the tool's purpose: extract and display embedded metadata from generated images. It specifies the actions (shows UUID, parameter hash, etc.) and differentiates from sibling tools like generate_image or edit_image by focusing on metadata retrieval.

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

Usage Guidelines4/5

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

The description indicates when to use the tool (on PNG/JPEG images with embedded OpenAI metadata) but does not explicitly state when not to use or provide alternatives. Since no other tool extracts metadata, the context is adequate.

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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