pruna-mcp-server

edit_image

Edit images by providing text instructions describing desired changes. Supports multiple images and customizable models.

Instructions

Edit one or more images with text instructions using Pruna AI.

Args: prompt: Edit instruction describing the desired changes images: 1-5 image URLs or local file paths model: Model to use (default: p-image-edit) aspect_ratio: Output aspect ratio seed: Random seed for reproducible generation

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	Default
`seed`	No
`model`	No	p-image-edit
`images`	Yes
`prompt`	Yes
`aspect_ratio`	No	match_input_image

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Jul 10, 2026

TDQS

A4.1/5.0

Behavior3/5

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

Annotations already indicate the tool is modifiable (readOnlyHint=false) and not destructive. The description adds that it uses 'Pruna AI' (external dependency) but does not elaborate on side effects, rate limits, or required permissions. Some value added beyond annotations.

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 concise, starting with a clear purpose sentence followed by a parameter list. Every sentence adds value, and the structure is easy to scan. No redundant or unnecessary text.

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?

The description covers the core functionality and parameters but omits details like valid model options, aspect ratio formats, error handling, output format, and prerequisites. Given the complexity and lack of output schema, more completeness would help an agent.

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

Parameters4/5

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

With schema description coverage at 0%, the description lists each parameter with a brief explanation (e.g., 'prompt: Edit instruction describing the desired changes'). This adds meaning beyond the schema's bare titles, though some params like aspect_ratio receive minimal clarification.

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 one or more images using text instructions, specifying the verb (edit) and resource (images) distinctly. This differentiates it from sibling tools like generate_image or generate_video, which create new content.

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 implies use when an existing image needs modification via a text prompt, and provides parameter docs like prompt and images. However, it does not explicitly state when not to use it or mention alternative tools for similar tasks.

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

Deploy Server