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Kling AI MCP Server by useapi.net (third-party)

Create an avatar

kling_create_avatar

Save a personal avatar from a portrait (imageUrl) for kling_avatar_video: its name, the prompt describing how it moves, and its voice (ttsSpeaker from kling_list_tts_voices, speed, emotion). Anything left out is suggested by Kling from the picture. Usually free. POST /avatars.

Input Schema

NameRequiredDescriptionDefault
emailNoThe Kling account email. Required when the token has several Kling accounts.
sceneNoUse case.
promptNoHow the avatar moves and looks when speaking.
imageUrlYesThe portrait: a public https URL, best one from kling_upload_asset (Kling must be able to fetch it).
nicknameNoName, up to 30 characters.
ttsSpeedNoVoice speed 0.8-2 (default 1).
ttsSpeakerNoThe voice's speakerId, from kling_list_tts_voices.
ttsEmotionKeyNoVoice emotion (default neutral), if the voice supports it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare a non-idempotent, non-destructive, open-world write. The description adds value beyond that: omitted fields are auto-suggested by Kling from the picture (server-side defaulting) and the operation is 'usually free' (cost behavior). It could still flag duplicate-creation risk from non-idempotency, but the added context is real.

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?

Two sentences, front-loaded with the verb and resource, with no wasted clauses. The closing cost note and endpoint round out the definition compactly.

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 create tool with no output schema, the description covers purpose, dependencies, defaults, and cost. It stops short of saying what the call returns (e.g., the avatar identifier to reuse in kling_avatar_video), which is the one remaining gap.

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 the schema already documents all eight fields. The description adds little beyond grouping the 'name, prompt, voice' bundle and noting defaults; the ttsSpeaker cross-reference it mentions is already in the schema text.

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 states a specific verb and resource (save a personal avatar from a portrait) and ties it to the downstream consumer, kling_avatar_video. It also names the sibling used to obtain the voice id (kling_list_tts_voices), so an agent can distinguish it from kling_save_voice, kling_create_element, and other creators.

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?

Clear usage context: create an avatar here to feed kling_avatar_video, and pull the voice id from kling_list_tts_voices. There is no explicit when-not or preference-among-alternatives guidance, but the dependency routing is unambiguous.

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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