Image Generation MCP Server

generate_image

Create custom images from text prompts using AI with adjustable size, quantity, and output format settings.

Instructions

Generate an image using Together AI API

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>"
    },
    "name": "generate_image"
  }
}

Input Schema

Name	Required	Description
`prompt`	Yes	Text prompt for image generation
`model`	No	Model to use for generation (default: black-forest-labs/FLUX.1-schnell-Free)
`width`	No	Image width (default: 1024)
`height`	No	Image height (default: 768)
`steps`	No	Number of inference steps (default: 1)
`n`	No	Number of images to generate (default: 1)
`response_format`	No	Response format (default: b64_json)
`image_path`	No	Optional path to save the generated image as PNG

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.7Jan 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the API provider but fails to describe critical behaviors like rate limits, authentication requirements, cost implications, error handling, or what happens when saving to 'image_path'. This leaves significant gaps for a tool with 8 parameters and no output schema.

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 extremely concise with a single sentence that directly states the tool's purpose. There is zero wasted language, and it's front-loaded with the core functionality, making it highly efficient.

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?

Given the complexity (8 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain return values, error cases, or behavioral nuances, leaving the agent with incomplete information for proper tool invocation in a real-world context.

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 fully documents all 8 parameters. The description adds no additional parameter semantics beyond what's already in the schema, meeting the baseline score of 3 for high schema coverage without extra value.

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 action ('Generate an image') and the target resource ('using Together AI API'), providing a specific verb+resource combination. However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or context for invocation. It simply states what the tool does without any usage instructions or exclusions.

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

Deploy Server

Other Tools

generate_imageC