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gemini_image_set

Generate a consistent set of images from a single master prompt, producing per-scene images or variations that keep the subject and style uniform. Maintains visual consistency across multiple related images.

Instructions

Generate a consistent SET of images: a master image from master_prompt, then one image per scene that references the master so the subject/style stays consistent. Provide scenes (explicit per-image prompts) OR count (variations of the master). Scene generations run in parallel (reference_mode "master", the default). On the hosted connector: saved characters and a saved style can seed the whole set by name, multi-image results include a bundle_url zip of every image (one curl instead of N), and max_wait_ms returns a pollable job handle if the batch runs long.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoSeed for reproducible generation; random if omitted
asyncNoRun in the background and return a job_id immediately instead of the image, so a long (Pro/4K) generation cannot hit the host tools/call timeout (-32001). Poll gemini_get_result with the job_id to fetch the result. PREFER `max_wait_ms` on the hosted connector: it runs where the executor is only guaranteed to stay alive while the request is open, so this option is served there as a bounded wait rather than an immediate hand-off.
countNoNumber of variations of master_prompt (when scenes omitted)
modelNoModel id override (default: server default; see gemini_list_models). gemini-3.1-flash-image (Nano Banana 2) is the versatile generalist workhorse — balances speed with state-of-the-art 4K generation, world knowledge, and reliable text rendering; excels at multi-reference-image processing and consistency. gemini-3-pro-image (Nano Banana Pro) is the premium choice for the most complex visual tasks — highest world knowledge, advanced localization, accurate brand consistency, precision creative control. gemini-3.1-flash-lite-image (Nano Banana 2 Lite) is the fastest/cheapest for simple tasks (1K only, no search grounding).
styleNoName of a saved style preset (see gemini_list_styles / gemini_save_style): its prompt fragment — and reference image, if it has one — is applied to the request automatically. Hosted connector only.
inlineNoReturn base64 images inline instead of writing to disk
scenesNoPer-image prompts (1-8); each references the master
confirmNoMust be true to proceed. Without this, the tool returns a preview.
basenameNoBase filename prefix for output images (default: slugified master_prompt)
charactersNoNames of saved characters (see gemini_list_characters / gemini_save_character): each one's reference image and description are attached to the request automatically, keeping recurring subjects consistent without re-sending anything. Hosted connector only.
image_sizeNoOutput resolution (512 = 0.5K, Flash-only)
output_dirNoDirectory to write images to (default: $GEMINI_OUTPUT_DIR or cwd)
timeout_msNoUpstream request timeout in ms for this call (default: $GEMINI_TIMEOUT_MS, else 60000 — or 120000 when image_size is 4K, which routinely runs past 60s)
max_wait_msNoWait up to this many ms for the result; if generation is still running when the budget expires, return { job_id, status: "running" } immediately instead (poll gemini_get_result). Keeps fast results in-band while a slow batch can never trip the host tools/call timeout (-32001) — e.g. 20000 for multi-image sets. Ignored when async is set.
orientationNoShape of the output, in plain terms: "landscape" (wide, 16:9), "portrait" (tall, 9:16) or "square" (1:1). Use this for a request phrased as landscape/portrait/vertical/horizontal. For any other proportion — 35mm photo (3:2), print (4:3), social (4:5), cinematic (21:9) — name it with aspect_ratio instead, which overrides this when both are given.
aspect_ratioNoExact output aspect ratio. For a plain landscape/portrait/square request, `orientation` is the shorthand; this wins if both are given.
google_searchNoGround the image in live Google Search results (current events, weather, data)
master_imagesNoReference image paths passed to the master generation call
master_promptYesPrompt for the master/reference image
from_clipboardNoUse the image currently on the macOS system clipboard as an input (downscaled to JPEG)
reference_modeNomaster: every image references the master (default). chain: each references the previous.
thinking_levelNoReasoning depth (Gemini 3 models); higher can help complex/structural edits
idempotency_keyNoOpaque idempotency key: a repeat call with the same key returns the recorded result (reused: true) instead of billing a new generation. Set it when retrying after a host timeout (-32001) to avoid a duplicate charge.
master_images_urlNoReference images passed to the master AND to every scene call (fetched once) as public https URLs — the SERVER downloads them, so no image bytes travel through the conversation. Preferred over images_base64, which costs ~14k tokens per photo and breaks if a file read was truncated. Max 15MB each; must be a directly-linked image (Content-Type image/*).
master_images_base64NoReference images as base64 strings or data URIs for master generation. Last resort: prefer master_images_url or master_images_file_uris, which keep image bytes out of the conversation
master_images_r2_keysNoReference images passed to the master AND to every scene call by r2_key from THIS connector's store: a signed upload (gemini_get_upload_url → curl PUT) or an earlier generation's media[].r2_key. The server reads its own bucket directly — no bytes in the conversation, no signed URL, no ~48h Files API expiry. Hosted connector only.
master_images_file_urisNoReference images passed to the master AND to every scene call by Gemini Files API reference ("files/<id>", or the full uri) from gemini_upload_file or POST /upload. Upload once, then reference it across as many calls as you like — no bytes are re-sent and none enter the conversation. Files are retained ~48h, after which the reference stops resolving.

Schema Changelog

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

  1. Changed2 schema fields changedv1.10.0
    • changedInput schema / properties / aspect_ratio / description
      Previous value: -"Output aspect ratio"New value: +"Exact output aspect ratio. For a plain landscape/portrait/square request, `orientation` is the shorthand; this wins if both are given."
    • addedInput schema / properties / orientation
      Added value: +{
      +  "description": "Shape of the output, in plain terms: \"landscape\" (wide, 16:9), \"portrait\" (tall, 9:16) or \"square\" (1:1). Use this for a request phrased as landscape/portrait/vertical/horizontal. For any other proportion — 35mm photo (3:2), print (4:3), social (4:5), cinematic (21:9) — name it with aspect_ratio instead, which overrides this when both are given.",
      +  "enum": [
      +    "landscape",
      +    "portrait",
      +    "square"
      +  ],
      +  "type": "string"
      +}
  2. Changed5 schema fields changedv1.7.0
    • changedInput schema / properties / async / description
      Previous value: -"Run in the background and return a job_id immediately instead of the image, so a long (Pro/4K) generation cannot hit the host tools/call timeout (-32001). Poll gemini_get_result with the job_id to fetch the result (jobs are per-process and expire ~10 min after completion)."New value: +"Run in the background and return a job_id immediately instead of the image, so a long (Pro/4K) generation cannot hit the host tools/call timeout (-32001). Poll gemini_get_result with the job_id to fetch the result. PREFER `max_wait_ms` on the hosted connector: it runs where the executor is only guaranteed to stay alive while the request is open, so this option is served there as a bounded wait rather than an immediate hand-off."
    • addedInput schema / properties / characters
      Added value: +{
      +  "description": "Names of saved characters (see gemini_list_characters / gemini_save_character): each one's reference image and description are attached to the request automatically, keeping recurring subjects consistent without re-sending anything. Hosted connector only.",
      +  "items": {
      +    "minLength": 1,
      +    "type": "string"
      +  },
      +  "maxItems": 8,
      +  "type": "array"
      +}
    • addedInput schema / properties / master_images_r2_keys
      Added value: +{
      +  "description": "Reference images passed to the master AND to every scene call by r2_key from THIS connector's store: a signed upload (gemini_get_upload_url → curl PUT) or an earlier generation's media[].r2_key. The server reads its own bucket directly — no bytes in the conversation, no signed URL, no ~48h Files API expiry. Hosted connector only.",
      +  "items": {
      +    "minLength": 1,
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • addedInput schema / properties / max_wait_ms
      Added value: +{
      +  "description": "Wait up to this many ms for the result; if generation is still running when the budget expires, return { job_id, status: \"running\" } immediately instead (poll gemini_get_result). Keeps fast results in-band while a slow batch can never trip the host tools/call timeout (-32001) — e.g. 20000 for multi-image sets. Ignored when async is set.",
      +  "exclusiveMinimum": 0,
      +  "maximum": 600000,
      +  "type": "integer"
      +}
    • addedInput schema / properties / style
      Added value: +{
      +  "description": "Name of a saved style preset (see gemini_list_styles / gemini_save_style): its prompt fragment — and reference image, if it has one — is applied to the request automatically. Hosted connector only.",
      +  "minLength": 1,
      +  "type": "string"
      +}
  3. First observedv1.2.0

TDQS

A4.5/5.0
Behavior4/5

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

With annotations only providing readOnlyHint=false and openWorldHint=true, the description adds substantial behavioral disclosure: scene generations run in parallel, the master seeds consistency, hosted-connector features like bundle_url zip downloads and pollable job handles, and max_wait_ms behavior when the budget expires. It also mentions the executor-lifetime constraint on the hosted connector. It doesn't detail every failure mode or auth requirement, but for a generative image tool the disclosed behaviors (parallelism, async vs bounded wait, zip output) are meaningful.

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?

The description is dense but efficient: it front-loads the core 'consistent SET' purpose, then packs workflow, defaults, parallel execution, hosted features, bundle_url, and max_wait_ms into three sentences. Every sentence earns its place. It is slightly long relative to the number of behavioral details, but the information density is high and no filler is present. It earns a 4 rather than 5 because the length is near the upper bound and some details (one curl instead of N) are minor.

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?

For a tool with 27 parameters and no output schema, the description captures the essential operational model: master-then-scenes, scenes vs count, parallel execution, hosted-connector features, and timeout/job-handle behavior. The absence of an output schema means the description could have described the return shape in more detail, but the input schema already documents parameters thoroughly. It is complete enough for an agent to call it correctly in the common hosted and local cases.

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?

Schema description coverage is 100%, so the baseline is 3, and the description adds value by explaining the relationship between scenes/count/master_prompt and the consistency workflow. It also contextualizes hosted-connector-only params like characters, style, and master_images_r2_keys. The description goes beyond the schema by clarifying defaults like reference_mode 'master' and when max_wait_ms is preferable to async. It doesn't restate every parameter, but it doesn't need to given full schema coverage.

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 phrase—'Generate a consistent SET of images'—and clearly distinguishes the tool from single-image generation by explaining the master-image-plus-scenes workflow. It also differentiates it from siblings like gemini_image_generate and gemini_image_edit by emphasizing consistency across multiple outputs. The mention of scenes, count, reference_mode, and bundle_url gives a concrete, non-tautological purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to provide `scenes` OR `count`, names the default reference_mode, and explains when to use hosted-connector features like saved characters/style and max_wait_ms. The `max_wait_ms` guidance also tells the agent when to prefer it over `async`, which is strong when-to-use guidance. This goes well beyond a vague 'use this for consistent sets' and includes concrete alternatives and conditions.

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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