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MCPGeneration-for-ElevenLabs

MCPGeneration-for-ElevenLabs

generate_dialogue_stream_with_timestamps

Stream multi-speaker dialogue via ElevenLabs and save audio with alignment timestamps for synced playback and captioning.

Instructions

Call the streaming dialogue endpoint with the documented alignment response and save audio plus timing metadata.

Input Schema

NameRequiredDescriptionDefault
inputsYes
filenameYes
model_idNo
allow_paidNo
future_textNo
language_codeNo
output_formatNomp3_44100_128
previous_textNo
allow_unknown_costNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It does disclose one side effect (audio plus timing metadata are saved to disk), but omits billing/cost behavior implied by allow_paid and allow_unknown_cost, streaming semantics, and where the file lands.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no wasted words, but the compactness comes at the cost of substance — the phrase 'documented alignment response' communicates nothing to an agent.

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

Completeness2/5

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

For a 9-parameter generation tool with no annotations, no output schema, and zero schema descriptions, this one-liner is far too thin. An agent would not know how to shape inputs, what costs may be incurred, or how timing metadata is returned.

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 description coverage is 0% across 9 parameters, so the description must compensate and does not. Only 'save audio plus timing metadata' loosely gestures at filename and timing output; inputs, voice_id, model_id, output_format, previous_text/future_text, and the two cost flags are entirely unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the operation (call the streaming dialogue endpoint) and states two outcomes (saved audio and timing metadata), which is more than a tautology. However, 'documented alignment response' is self-referential filler, and it never distinguishes this tool from the four sibling variants (generate_dialogue, generate_dialogue_stream, generate_dialogue_with_timestamps).

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 statement of when to choose the streaming variant over the non-streaming or non-timestamp siblings, and no mention of prerequisites. An agent must infer selection purely from the name suffix.

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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