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AI Manga & Anime Generator - Mangii MCP

Continue manga story

manga.continue_story

Add the next panel. Do not send style_id. Defaults: Image 1 = first panel (identity), Image 2 = last distinct panel (scene). Override via manga.list_panels then identity_panel_id or identity_image and/or continuity_panel_id or continuity_image. Same credit costs as create.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoOn this MCP server the default is false: wait and return image_url in one call. Set true only if you will poll manga.get_job. HTTP API default remains async.
promptYesScene in everyday language: characters, place, action, mood, camera, weather, color or black-and-white. Example: "A duel under cherry blossoms, low angle, rain, full color." Max 2000 characters.
qualityNoGeneration quality. standard costs 1 credit, hd 2, ultra 5. Default standard. HD/Ultra need an unlocked API wallet.
story_idYesStory id from manga.create_story. Example: a Firestore story document id returned as story_id.
identity_imageNoReplacement photo: https URL or data:image/...;base64,... URI. Public hosts only. Same slot cannot also send a panel id.
idempotency_keyNoOptional. Reuse the same key on retry so a timeout does not charge twice. 8-200 chars. Omit to mint a one-shot key (unsafe on retry).
reference_imageNoAlias for identity_image. Replaces Image 1 with an uploaded photo or URL.
continuity_imageNoReplacement Image 2 (scene) photo: https URL or data URI. Do not also send continuity_panel_id.
context_panel_idsNoLegacy list override [identity_panel_id, scene_panel_id]. Ignored when identity_* or continuity_* fields are set. Prefer those named slots.
identity_panel_idNoOverride Image 1 (identity) with this panel id from manga.list_panels. Do not also send identity_image.
continuity_panel_idNoOverride Image 2 (scene) with this panel id from manga.list_panels. Do not also send continuity_image.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoMachine error code such as invalid_request, insufficient_credits, or quality_forbidden.
job_idNoAsync job id when async is true or the work is still running.
messageNoHuman-readable error. Never includes stack traces or internal paths.
qualityNoQuality used for this generation.
panel_idNoGenerated or regenerated panel id.
story_idNoCreated or existing story id.
image_urlNoHTTPS URL of the finished panel when async is false and generation succeeded.
next_stepNoWhat the agent should call next. Follow this instead of guessing.
request_idNoRequest correlation id.
credits_chargedNoAPI credits billed for a successful generation.
credits_remainingNoRemaining spendableCredits after the call (apiPack plus purchase-backed packs).

TDQS

A4.1/5.0
Behavior4/5

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

Annotations indicate write-safe behavior but not specifics. The description adds meaningful behavior: defaults for Image 1/Image 2, override paths, the style_id exclusion, and credit-cost relationship to create. It does not state the exact mutation extent or what happens to the existing story, but the annotations plus the add-panel principle cover the core safety profile. This is solidly transparent without being verbose.

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?

Four short sentences carry a dense but efficient payload: purpose, one caution, defaults, and override workflow. Nothing is redundant or bloated. The main directive is front-loaded and the operational detail follows logically.

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?

This is a complex tool with 11 parameters and several override relationships. The description covers the central behavioral model, the alternatives, and the cost relationship; the schema fills in parameter-level constraints and default behavior. It doesn't discuss the async/poll flow or the returned data, but the schema-annotated output schema and async doc in the property handle that. All critical decision-making context is present.

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?

Input schema describes every parameter, so the baseline is 3. The description uniquely adds cross-parameter context: it defines Image 1 as the identity slot and Image 2 as the scene slot, gives the default from-panel list, and explains how identity_image/continuity_image relate to the panel ids. That meaningfully exceeds what each individual parameter description provides, earning a higher score.

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?

The description's opening 'Add the next panel' names a specific action upon a specific resource, making the tool's purpose immediately recognizable as continuation, not creation or regeneration. It does not explicitly contrast with siblings like regenerate_panel or create_story, but the defaults-and-overrides framing clarifies its role. A direct sibling comparison would push this to a 5.

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 practical when-to-use guidance: 'Override via manga.list_panels' shows the recommended workflow, 'Do not send style_id' gives a concrete exclusion, and 'Same credit costs as create' sets expectations. It implicitly says this is for adding the next panel, but it stops short of explicitly stating when to prefer this over regenerate_panel or create_story. That missing explicit alternative comparison keeps it from a 5.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: story creation, continuation, regeneration, panel listing, story listing, style listing, credit lookup, credit purchase, and job polling. Even the credit-related tools are clearly separated by purchase versus query. There is no meaningful overlap that would confuse an agent.

Naming Consistency5/5

All tools consistently use the manga. prefix with snake_case verb_noun names like create_story, list_panels, and regenerate_panel. The pattern is uniform across the entire set, making the API predictable and easy to navigate.

Tool Count5/5

Nine tools is a well-scoped size for a manga generation server: three creation-oriented tools, three listing tools, two credit tools, and one async job helper. Each tool serves a clear, non-redundant role in the workflow.

Completeness4/5

The core manga creation lifecycle is well covered: create, continue, regenerate, list stories, and list panels, plus style discovery and credit management. The only notable gaps are destructive operations like deleting stories or panels and perhaps a story detail endpoint, but these are not essential to the primary generation workflow.