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Media Toolkit MCP Server

Media Toolkit MCP Server

by kevinten-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

convert_format

Convert images to PNG, JPG, or WebP format, including SVG rasterization to PNG, using local processing.

Instructions

Convert an image between formats: PNG, JPG, WebP, or SVG to PNG. Works locally with Pillow. Note: SVG input is rasterized to PNG via cairosvg if available, otherwise Pillow.

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": {
      "image_path": "<image_path>",
      "output_format": "<output_format>"
    },
    "name": "convert_format"
  }
}

Input Schema

NameRequiredDescriptionDefault
image_pathYesPath to the input image file
output_pathNoPath to save the output image (optional, auto-generated if omitted)
output_formatYesTarget format

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions local execution and SVG rasterization, but does not address file overwrites, size limits, library dependencies beyond Pillow, or any destructive aspects.

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?

Two sentences plus a note—efficient and to the point. No filler, but could be more structured with explicit input/output format mapping.

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?

Missing important details like return value, error handling, and supported input formats explicitly (only implied). The ambiguity about SVG conversion to non-PNG outputs and lack of output format clarification reduces completeness.

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 baseline is 3. The description adds no extra meaning to parameters beyond the schema; it only provides a note on SVG conversion behavior, which is more about overall process than parameter semantics.

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?

Clearly states it converts images between formats, names specific formats, and notes local processing with Pillow. However, the phrase 'or SVG to PNG' is slightly ambiguous about input-output combinations, and it doesn't differentiate from siblings.

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 on when to use this tool vs alternatives like resize_image or remove_background. The description only states what it does, leaving the agent to infer context from sibling names.

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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