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elevenlabs-mcp

elevenlabs-mcp

by neomorrison
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_history

Retrieve recent audio generation history with filters for voice ID and search text.

Instructions

List recent generation history items.

Args: page_size: number of items to return. voice_id: filter to a specific voice. search: free-text search over history.

Returns a JSON summary of history items.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
searchNo
voice_idNo
page_sizeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, and the description does not disclose behavioral traits such as whether the tool is idempotent, pagination behavior, or rate limits. It only states it returns a JSON summary, which is insufficient.

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 concise and front-loaded with the primary purpose. It uses a clear structure with Args and Returns, though it could be slightly more efficient.

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?

The description covers the basics but lacks details on sorting, default ordering, or pagination behavior. Since an output schema exists, the return format is not critical, but additional context would improve completeness.

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?

The description adds brief explanations for each parameter (e.g., 'filter to a specific voice' for voice_id), but does not cover all details like data types or constraints. Given 0% schema coverage, more detail would be beneficial.

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 clearly states the verb 'list' and resource 'generation history items', distinguishing it from sibling tools like 'get_history_item' and 'delete_history_item'.

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

Usage Guidelines3/5

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

The description lists parameters but does not explicitly state when to use this tool vs alternatives (e.g., get_history_item for a single item). Usage context is implied rather than explicit.

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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