Skip to main content
Glama
falahgs

image-gen3-google-mcp-server

by falahgs

generate_images

Generate images from text descriptions using Google's Imagen 3.0 model. Supports multiple images per request and automatic file saving.

Instructions

Generate images using Google Gemini AI

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText description of the image to generate
numberOfImagesNoNumber of images to generate (1-4)
outputDirNoDirectory to save generated imagesG:\image-gen3-google-mcp-server\images
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only states that images are generated, but omits key traits such as whether the tool saves files to disk (though implied by 'outputDir' in schema), cost implications, rate limits, or error behavior. The agent learns little beyond the basic purpose.

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 a single sentence achieving conciseness, but it lacks structure and front-loading of critical constraints. It does not highlight the image count range (1-4) or output directory default, which are important for usage but are buried in the schema.

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

Completeness2/5

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

The tool has no output schema, so the description should explain what the tool returns (e.g., file paths, base64 data). It does not. Given the sibling tool suggesting alternative image-related functionality, more context on output format and typical use cases would be beneficial.

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 coverage is 100%, so the schema already documents all parameters. The description adds the context of using 'Google Gemini AI', which is not in the schema. However, it does not clarify or enrich the parameter meanings beyond the schema descriptions. Baseline of 3 is appropriate.

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 action ('generate images') and specifies the service ('Google Gemini AI'). It effectively distinguishes from the sibling 'create_image_html' tool by indicating this generates actual images rather than HTML.

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 is provided on when to use this tool versus the sibling 'create_image_html'. There are no conditions, prerequisites, or exclusions mentioned, leaving the agent to infer context from the tool name alone.

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/falahgs/image-gen3-google-mcp-server'

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