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dnshtm9

kenari-media-mcp

by dnshtm9

Generate Image

generate_image

Turn text prompts into PNG/JPG images via Kenari Media API, save them to your output directory, and get absolute file paths while managing per-image IDR costs.

Instructions

Generate image(s) via POST /v1/images/generations. Saves PNG/JPG to KENARI_OUTPUT_DIR and returns absolute path(s). Costs IDR per image — check list_media_models first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoHow many images to generate (integer >= 1). Defaults to 1. Capped by KENARI_MAX_IMAGE_N (default 4). Each image costs IDR.
sizeNoImage dimensions, e.g. '1024x1024'. Optional and model-dependent.
modelYesKenari image model id, e.g. 'gpt-image-2'. Call list_media_models first for exact ids and per-image IDR costs.
promptYesWhat to generate. Be specific and descriptive for best results.
previewNoRequest lower-quality previews. Files are still saved and no base64 is returned. Does NOT reduce Kenari cost.
backgroundNoBackground handling: 'transparent', 'opaque', or 'auto'. Optional; not all models support transparency.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoKenari video job id, when relevant to the result or error.
opNoTool operation name the error occurred in.
codeNoMachine-readable code: an error code (e.g. unauthorized, bad_request, upstream_error) or a state marker (e.g. rendering, done, still_rendering).
hintNoHuman-readable remediation hint (e.g. set KENARI_API_KEY).
countNoNumber of images saved.
modelNoKenari image model id used.
pathsNoAbsolute local paths of the saved image files under KENARI_OUTPUT_DIR.
statusNoHTTP status number (on API errors) or the Kenari job status string (on video status results).
disabledNoTrue when video tools are disabled via KENARI_ALLOW_VIDEO=0.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations establish that this is a write operation but non-destructive. The description adds valuable behavioral detail beyond the annotations: it saves PNG/JPG files to KENARI_OUTPUT_DIR, returns absolute paths, and incurs monetary cost. This gives the agent practical expectations about side effects.

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 compact and front-loaded, covering purpose, mechanism, output location, return value, and cost guidance in two sentences. Every clause contributes useful information without repetition or filler.

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

Completeness5/5

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

Given the fully described schema, existing output schema, and annotations, the description supplies the missing operational context: where files go, what is returned, and a prerequisite to check list_media_models. An agent has enough to call this tool correctly without ambiguity.

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 baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides; the cost and model-id guidance mirrors the model parameter description. It does not harm or clarify individual params further.

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: 'Generate image(s)' and gives the exact API endpoint, POST /v1/images/generations. It clearly distinguishes this from sibling tools like edit_image and create_video by stating it creates images and saves them to disk.

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 gives clear context: use this to generate images, expect per-image IDR costs, and check list_media_models first for model IDs and pricing. It does not explicitly contrast with edit_image or state when to avoid this tool, but the context is strong enough for an agent to select it appropriately.

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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