Skip to main content
Glama

inpaint

Fill masked regions of an image with AI-generated content using a text prompt. Provide input image, mask, and prompt to regenerate selected areas.

Instructions

Fill in masked regions of an image with AI-generated content.

All parameters except prompt, input_image, and mask_image are optional with sensible defaults. Change any parameter to customize.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cfgNoGuidance scale. Default: 8.0. Typical: 1.0-20.0.
seedNoRandom seed. Default: -1 (random).
stepsNoSampling steps. Default: 20. Typical: 15-50.
promptYesText description of what to generate in the masked area.
denoiseNoDenoising strength for inpainted area. Default: 1.0. Range: 0.0-1.0.
samplerNoSampler algorithm. Default: "euler". Use list_samplers_and_schedulers() to see all.euler
schedulerNoNoise scheduler. Default: "normal". Use list_samplers_and_schedulers() to see all.normal
checkpointNoCheckpoint model. Default: "" (auto-selects). Use list_models(folder="checkpoints") to see options.
mask_imageYesFilename of the mask image. White areas will be inpainted.
input_imageYesFilename of the source image in ComfyUI's input directory.
grow_mask_byNoPixels to expand the mask boundary for smoother blending. Default: 6. Range: 0-64.
negative_promptNoThings to avoid. Default: "" (none).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the operation ('fill in') and parameter optionality. It does not disclose that this is a generative, potentially non-deterministic operation, how long it may take, whether it blocks, or that it returns an image. The phrase 'Change any parameter to customize' adds minimal behavioral context.

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 two sentences: the first states the core function, the second clarifies parameter optionality. No filler or redundancy; it is appropriately front-loaded and earns its place.

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 moderate complexity (12 parameters, 3 required), the description, combined with 100% schema coverage and an output schema, is adequate. It clearly identifies the core action and parameter defaults. It could mention the need for both source and mask images, but this is already explicit in the schema's required fields and parameter descriptions.

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 the baseline is 3. The description adds value by stating that all parameters except the three required ones are optional with sensible defaults, which helps an agent avoid unnecessary configuration. However, it does not elaborate on any individual parameter beyond what the schema already states.

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 opens with a specific verb-object pair ('Fill in masked regions of an image with AI-generated content'), clearly identifying the tool's purpose and distinguishing it from image generation or upscaling siblings. The scope is well-defined through the reference to masks.

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?

The description implies usage in contexts where an image has masked regions to fill, but it provides no explicit guidance on when to choose this tool over alternatives like image_to_image or text_to_image. No exclusions or alternative tool mentions are given.

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/halbert04/comfyui-mcp'

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