Gemini MCP Server

Edit Image with Gemini

edit_image

Edit images by providing natural-language instructions. Returns edited image with preview and saves full-resolution to disk.

Instructions

Edit one or more images using Google Gemini image models (Nano Banana Pro). Provide images and natural-language instructions for how to modify them. Returns edited image with inline preview and saves full-resolution to disk.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>",
      "images": "<images>"
    },
    "name": "edit_image"
  }
}

Input Schema

Name	Required	Description
`prompt`	Yes	Instructions for how to edit the image(s)
`images`	Yes	One or more images to edit
`model`	No	Gemini image model to use (default: gemini-3-pro-image-preview)
`use_search`	No	Enable Google Search grounding for data-driven editing
`global_media_resolution`	No	Global image quality setting (default: HIGH). See generate_image for details.
`outputPath`	No	Optional file path to save the edited image (e.g., ./output/edited.png)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.3.0Jun 22, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It mentions returning an inline preview and saving to disk, but does not disclose potential side effects or requirements like authentication. Adequate but not detailed.

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 two sentences, clearly front-loaded with the core action. Every sentence adds value, though could be structured with bullet points for better readability.

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

Completeness3/5

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

For a tool with 6 parameters and no output schema, the description partially addresses return values (inline preview, save to disk). However, it does not specify response structure or additional context like default save locations, leaving gaps.

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 schema provides detailed parameter meanings. The description adds no further parameter details beyond the schema, hence baseline score of 3.

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 images using Gemini models, with natural language instructions. It distinguishes itself from siblings like generate_image (creates) and analyze_image (analyzes).

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 for editing images with natural language, but does not provide explicit when-to-use or when-not-to-use guidance. It lacks differentiation from similar tools like generate_image for image creation tasks.

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