Jump to content

Connect SuperML | Leeroopedia MCP: Equip your AI agents with best practices, code verification, and debugging knowledge. Powered by Leeroo — building Organizational Superintelligence. Contact us at founders@leeroo.com.

Implementation:Elevenlabs Elevenlabs python VoicesClient Search

From Leeroopedia
Knowledge Sources
Domains Speech_Synthesis, Voice_Management
Last Updated 2026-02-15 00:00 GMT

Overview

Concrete tool for searching and filtering available voices with pagination provided by the elevenlabs-python SDK.

Description

The VoicesClient.search method queries the ElevenLabs v2 voices endpoint to retrieve voices matching specified criteria. It supports full-text search across name, description, and labels, filtering by voice type and category, sorting by creation date or name, and paginated results. This is the recommended method for voice discovery (over get_all which returns the legacy v1 response).

Usage

Use this method when you need to find a specific voice by name or characteristics, list all voices of a particular type, implement voice selection UI with pagination, or fetch specific voices by their IDs.

Code Reference

Source Location

Signature

def search(
    self,
    *,
    next_page_token: typing.Optional[str] = None,
    page_size: typing.Optional[int] = None,
    search: typing.Optional[str] = None,
    sort: typing.Optional[str] = None,
    sort_direction: typing.Optional[str] = None,
    voice_type: typing.Optional[str] = None,
    category: typing.Optional[str] = None,
    fine_tuning_state: typing.Optional[str] = None,
    collection_id: typing.Optional[str] = None,
    include_total_count: typing.Optional[bool] = None,
    voice_ids: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None,
    request_options: typing.Optional[RequestOptions] = None,
) -> GetVoicesV2Response:
    """
    Gets a list of all available voices for a user with search,
    filtering and pagination.
    """

Import

from elevenlabs import ElevenLabs

client = ElevenLabs()
# Access via: client.voices.search(...)

I/O Contract

Inputs

Name Type Required Description
search Optional[str] No Full-text search across name, description, labels
voice_type Optional[str] No Filter: 'personal', 'community', 'default', 'workspace', 'non-default', 'saved'
category Optional[str] No Filter by voice category
page_size Optional[int] No Max results per page (up to 100, default 10)
next_page_token Optional[str] No Pagination token from previous response
sort Optional[str] No Sort field: 'created_at_unix' or 'name'
sort_direction Optional[str] No 'asc' or 'desc'
voice_ids Optional[Union[str, Sequence[str]]] No Fetch specific voice IDs
fine_tuning_state Optional[str] No Filter by fine-tuning state
collection_id Optional[str] No Filter by collection
include_total_count Optional[bool] No Include total count in response

Outputs

Name Type Description
(return) GetVoicesV2Response Contains list of Voice objects with voice_id, name, labels, settings, plus pagination info (has_more, next_page_token)

Usage Examples

Search by Name

from elevenlabs import ElevenLabs

client = ElevenLabs()

# Search for voices matching "Rachel"
response = client.voices.search(search="Rachel")
for voice in response.voices:
    print(f"{voice.name}: {voice.voice_id}")

Filter by Type with Pagination

from elevenlabs import ElevenLabs

client = ElevenLabs()

# Get personal voices, 20 per page
response = client.voices.search(
    voice_type="personal",
    page_size=20,
    sort="created_at_unix",
    sort_direction="desc",
)

# Paginate
while response.has_more:
    response = client.voices.search(
        voice_type="personal",
        page_size=20,
        next_page_token=response.next_page_token,
    )

Fetch Specific Voice IDs

from elevenlabs import ElevenLabs

client = ElevenLabs()

# Fetch specific voices by ID
response = client.voices.search(
    voice_ids=["JBFqnCBsd6RMkjVDRZzb", "21m00Tcm4TlvDq8ikWAM"]
)

Related Pages

Implements Principle

Requires Environment

Page Connections

Double-click a node to navigate. Hold to expand connections.
Principle
Implementation
Heuristic
Environment