Skip to main content
Glama
hedging8563

TokenLab MCP Server

by hedging8563

Edit image

edit_image

Edit images by uploading files, providing URLs, or using JSON image references. Supports model selection, masking, and various output options.

Instructions

Edit image Edits an image using multipart image uploads, JSON image URLs, or the official JSON images array for supported GPT Image models.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
maskNoOptional JSON mask reference for image edits. Provide exactly one of image_url or file_id. Multipart requests can also send mask as a file part.
sizeNo
userNo
asyncNoReturn a task before the edited image is ready for models that support public async execution.
modelYesModel to use for image edits. Send this explicitly.
imagesNoOfficial JSON image references for image edits. Provide exactly one of image_url or file_id for each item. GPT Image edits accept up to 16 source images; xAI Grok Imagine edit models accept at most 3 source images.
promptYes
qualityNo
image_urlNoSingle source image URL. Kept for TokenLab compatibility; use images for the official JSON shape.
backgroundNo
image_urlsNoMultiple source image URLs. GPT Image edits accept up to 16 source images; xAI Grok Imagine edit models accept at most 3 source images.
moderationNo
resolutionNo
compressionNo
aspect_ratioNo
output_formatNo
response_formatNo
output_compressionNo
Behavior2/5

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

Annotations indicate readOnlyHint=false (mutation) and openWorldHint=true (accepts extra parameters), but the description adds little beyond mentioning input methods. It does not disclose behavior like error handling, rate limits, or side effects.

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

Conciseness3/5

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

The description is short but contains redundancy (repeating 'Edit image' in the first sentence). It could be more concise but is not overly verbose.

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?

With 19 parameters, nested objects, no output schema, and low schema coverage, the description is woefully incomplete. It does not explain return values, required parameter combinations, or constraints.

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 32%, and the description fails to explain the many undocumented parameters. It only mentions the three input methods, leaving agents unclear on how to use size, quality, background, etc.

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 clearly states the tool edits images and mentions three input methods (multipart, JSON URLs, images array) for supported GPT Image models. However, it does not explicitly distinguish this tool from sibling tools like create_image or edit_image_file.

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?

No guidance on when to use this tool vs other image-related tools. The description does not specify prerequisites, recommended scenarios, or when to choose alternative tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/hedging8563/tokenlab-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server