pictor-mcp

Apply an ordered image pipeline

image_transform

Run multiple image transformations—resize, crop, rotate, watermark, background removal, and more—in a single call, so the image is transferred once and processed entirely server-side.

Instructions

Run several operations in one call, in order. Prefer this over chaining single-step tools: it transfers the image once and applies every step server-side. Operations: auto_orient, resize, crop, rotate, flip, sharpen, blur, smart_crop, watermark_text, watermark_image, background_remove, feather.

Input Schema

TableJSON Schema

Name	Required	Description
`url`	No	http(s) URL to fetch (disabled by default).
`path`	No	Path to the image, inside an allowed input root.
`quality`	No	Lossy quality for the final encode.
`lossless`	No	Use a lossless encode where supported.
`operations`	Yes	Ordered list of operations, each with an 'op' field.
`base64_data`	No	Inline base64 image, optionally a data: URI.
`output_name`	No	Override the output filename.
`return_image`	No	Embed the result inline for vision clients.
`output_format`	No	Output codec; defaults to the input format.
`return_base64`	No	Include base64 in the JSON result.
`strip_metadata`	No	Strip EXIF/GPS metadata from the output.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	No
`input`	No	Summary of the source image, when one was read.
`notes`	No
`steps`	No
`metrics`	No	Operation-specific measurements (e.g. comparison scores).
`outputs`	No
`operation`	Yes	Tool that produced this result.
`sizeChange`	No
`inlineImageIncluded`	No	True when an image block accompanies this result for vision-capable clients.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 15, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations present, the description carries the behavioral burden. It discloses that operations are applied in order and that the image is transferred once and processed server-side, which is useful performance context. However, it omits details about failure modes, operation limits, or input source constraints, though those are present in the 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 two sentences. The first sentence states the core purpose, the second explains when to prefer it and lists the supported operations. No words are wasted, and the key differentiator (single transfer, server-side ordering) is front-loaded.

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

Completeness4/5

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

The description provides a clear overview of the tool's role and the available operations. While it does not mention constraints like the 32-operation maximum, that information is present in the schema. Given the existence of an output schema, the description does not need to explain return values, making it adequate for an agent to select and invoke the tool correctly.

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?

All parameters have descriptions in the schema (100% coverage), so the baseline is 3. The description lists the available operations, but that list is also encoded in the schema's discriminator and operation definitions. The description adds no detail about parameter formats or defaults beyond what the schema already provides.

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 opens with a specific verb and resource: 'Run several operations in one call, in order.' This clearly states the tool's function (applying an ordered pipeline) and differentiates it from siblings that perform a single operation, such as image_resize or image_crop. The line 'Prefer this over chaining single-step tools' makes the distinction explicit.

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 explicitly recommends using this tool over chaining individual transform tools, and explains the benefit (single transfer, server-side execution). It does not explicitly state a when-not scenario, such as 'for a single operation use the dedicated tool,' but the guidance effectively routes the agent to this tool for multi-step processing.

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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