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jashwanth0712

RunPod Image MCP Server

edit_image

Describe desired changes to edit images using AI. Adjust style, background, add or remove elements, enhance quality.

Instructions

Edit or transform images using Nano Banana Pro Edit API.

This tool applies AI-powered edits to existing images based on text descriptions.
You can adjust style, add/remove elements, change backgrounds, enhance quality, etc.

Args:
    prompt: Description of desired edits or transformations. Be specific about
        what changes you want (e.g., "change background to sunset", "add studio
        lighting", "remove watermark", "enhance colors").
    image_urls: List of 1-10 publicly accessible image URLs to edit.
        Images must be reachable via HTTP/HTTPS. Common formats supported: JPEG, PNG, WebP.
    resolution: Output resolution. Options:
        - "1k": Lower resolution, faster processing ($0.14)
        - "2k": Standard resolution, best value ($0.14) [default]
        - "4k": High resolution for detailed work ($0.24)
    aspect_ratio: Output aspect ratio (optional). If not specified, maintains original.
        Options: "1:1" (square), "16:9" (landscape), "9:16" (portrait), "3:2", "2:3",
        "4:3", "3:4", "4:5", "5:4", "21:9"
    output_format: Output file format. Options:
        - "jpeg": Smaller file size, good for photos (default)
        - "png": Lossless quality, good for graphics
    enable_base64_output: Return base64-encoded image data instead of URL.
        Default: false (return URL)
    enable_sync_mode: Enable synchronous mode for immediate processing.
        Default: false (asynchronous processing)
    max_wait_seconds: Maximum time to wait for job completion in seconds.
        Default: 300 (5 minutes)

Returns:
    Success message with edited image URL, resolution, cost, and job ID.
    Format: "✓ Image edited successfully!

URL: ... Resolution: ... Cost: $... Job ID: ..."

Examples:
    - "Add dramatic sunset lighting to this portrait"
    - "Remove background and replace with solid white"
    - "Enhance colors and increase sharpness for product photography"
    - "Transform into oil painting style while keeping the subject"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
image_urlsYes
resolutionNo2k
aspect_ratioNo
output_formatNojpeg
enable_base64_outputNo
enable_sync_modeNo
max_wait_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description fully discloses behavior: returns URL/base64, supports sync/async modes, cost per resolution, and return format. It does not mention side effects like whether original images are preserved, but overall it is transparent about key behaviors.

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

Conciseness4/5

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

The description is organized with Args, Returns, and Examples sections, making it easy to parse. It is somewhat lengthy but each sentence adds value (e.g., parameter details, cost info, return format). Could be slightly trimmed without losing clarity.

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

Completeness5/5

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

Given the tool's complexity (8 parameters, no annotations, but presence of output schema), the description is highly complete. It covers all parameters, provides usage examples, explains output format, and mentions cost. The agent has sufficient information to use the tool correctly.

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

Parameters5/5

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

The input schema has 0% description coverage (no parameter descriptions), but the tool description compensates fully by detailing each parameter: prompt with examples, image_urls constraints, resolution options with costs, aspect_ratio list, output_format, and boolean/integer flags. This adds significant meaning beyond the schema.

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 edits or transforms images using an API, distinguishing it from siblings like generate_image (creates new images) and check_job_status (checks job status). The verb 'edit' and resource 'images' are specific.

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 provides examples of when to use (e.g., 'Add dramatic sunset lighting'), implying the tool is for editing existing images. However, it lacks explicit when-not-to-use guidance or direct alternatives (e.g., 'for creating new images, use generate_image'). The context is clear but not exhaustive.

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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