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@runapi.ai/elevenlabs-mcp

by runapi-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

text_to_dialogue

Generate multi-speaker dialogue audio from text using ElevenLabs via RunAPI. Submit dialogue turns to create a task, then poll status and retrieve output URLs.

Instructions

Create a ElevenLabs task on RunAPI (text to dialogue). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
dialogueYesDeclared type: array.
stabilityNoDeclared type: number. Known values: 0, 0.5, 1.
timeout_msNo
callback_urlNoDeclared type: string.
language_codeNoDeclared type: string.
poll_interval_msNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed9 schema fields changedv0.2.0
    • changedInput schema / additionalProperties
      Previous value: -falseNew value: +{}
    • addedInput schema / properties / callback_url / description
      Added value: +"Declared type: string."
    • addedInput schema / properties / dialogue / description
      Added value: +"Declared type: array."
    • addedInput schema / properties / language_code / description
      Added value: +"Declared type: string."
    • removedInput schema / properties / model / enum
      Removed value: -[
-  "text-to-dialogue-v3"
-]
    • addedInput schema / properties / poll_interval_ms / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / stability / description
      Added value: +"Declared type: number. Known values: 0, 0.5, 1."
    • removedInput schema / properties / stability / enum
      Removed value: -[
-  0,
-  0.5,
-  1
-]
    • addedInput schema / properties / timeout_ms / maximum
      Added value: +9007199254740991
  2. Changed5 schema fields changedv0.1.7
    • addedInput schema / properties / callback_url
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / dialogue / items
      Added value: +{}
    • addedInput schema / properties / dialogue / type
      Added value: +"array"
    • addedInput schema / properties / language_code
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "dialogue"
+]
  3. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the async task contract by stating it returns a task id, status, and output URLs. However, it says nothing about cost/billing, auth requirements, failure modes, or how `wait`/polling affects behavior.

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?

Two short sentences, front-loaded with the action and resource, with the return contract appended. Only minor issue is the awkward 'a ElevenLabs' phrasing; no wasted content.

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

Completeness3/5

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

For an 8-parameter, no-annotation, no-output-schema tool, the description partially compensates by describing the return payload. It leaves opaque parameters (dialogue structure, language_code, callback_url semantics) and async/timeout behavior unaddressed, so it is only minimally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75%, below the high-coverage baseline, and the description adds no parameter detail. The single required parameter `dialogue` is documented only as 'Declared type: array' with no item shape, so an agent gets no help on the most critical input.

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?

States a clear verb ('Create') plus resource ('ElevenLabs task on RunAPI') and qualifies it as text-to-dialogue, which loosely distinguishes it from text_to_speech and text_to_sound. It does not explicitly name those siblings, so differentiation is left implicit.

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

Usage Guidelines2/5

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

There is no guidance on when to choose dialogue synthesis over text_to_speech or text_to_sound, no prerequisites, and no mention of the related get_task follow-up for retrieving results. Usage must be inferred entirely from the tool name.

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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