Skip to main content
Glama
brandon-fryslie

elevenlabs-mcp

search_voices

Read-only

Search your ElevenLabs voice library by name, description, labels, or category. Filter results and sort by name or creation date to find the voice you need.

Instructions

Search for existing voices, a voice that has already been added to the user's ElevenLabs voice library.
Searches in name, description, labels and category.

Args:
    search: Search term to filter voices by. Searches in name, description, labels and category.
    sort: Which field to sort by. `created_at_unix` might not be available for older voices.
    sort_direction: Sort order, either ascending or descending.

Returns:
    List of voices that match the search criteria.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNo
sortNoname
sort_directionNodesc

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The search_voices tool function that calls client.voices.search() and maps results to McpVoice objects.
    def search_voices(
        search: str | None = None,
        sort: Literal["created_at_unix", "name"] = "name",
        sort_direction: Literal["asc", "desc"] = "desc",
    ) -> list[McpVoice]:
        response = client.voices.search(
            search=search, sort=sort, sort_direction=sort_direction
        )
        return [
            McpVoice(id=voice.voice_id, name=voice.name, category=voice.category)
            for voice in response.voices
        ]
  • The @mcp.tool decorator that registers search_voices as an MCP tool.
    @mcp.tool(
        annotations=ToolAnnotations(readOnlyHint=True, openWorldHint=True),
        description="""
        Search for existing voices, a voice that has already been added to the user's ElevenLabs voice library.
        Searches in name, description, labels and category.
    
        Args:
            search: Search term to filter voices by. Searches in name, description, labels and category.
            sort: Which field to sort by. `created_at_unix` might not be available for older voices.
            sort_direction: Sort order, either ascending or descending.
    
        Returns:
            List of voices that match the search criteria.
        """
    )
  • The McpVoice Pydantic model used as the return type for search_voices.
    class McpVoice(BaseModel):
        id: str
        name: str
        category: str
        fine_tuning_status: Optional[Dict] = None
Behavior4/5

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

Annotations already indicate a safe read operation (readOnlyHint) and variable results (openWorldHint). The description adds value by noting that sorting by 'created_at_unix' may not be available for older voices, a behavioral trait not covered by annotations. This is helpful for agent decision-making.

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?

The description is concise (3 sentences) and front-loaded with the core purpose. Every sentence provides necessary information without redundancy. No unnecessary words or filler.

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?

Given the tool's simplicity (3 parameters, list output) and the presence of an output schema, the description covers purpose, parameters, and a key behavioral detail. While it lacks mention of pagination or result limits, the openWorldHint annotation mitigates this. It is complete enough for reliable invocation.

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

Parameters5/5

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

The input schema has 0% description coverage, so the description fully compensates by explaining each parameter's purpose and behavior. For example, it notes that search filters name, description, labels, and category, and that sort direction orders results. This adds essential meaning beyond the schema's enum values.

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 explicitly states the tool searches for voices already in the user's ElevenLabs voice library, differentiating it from public library searches. It specifies searchable fields (name, description, labels, category), making the purpose precise and distinct from siblings like search_voice_library.

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 implies usage for the user's own voices but does not explicitly compare to alternatives or provide when-not-to-use guidance. The context is clear but lacks direct directives or exclusions, making it adequate but not exemplary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/brandon-fryslie/vibedungeon-voice'

If you have feedback or need assistance with the MCP directory API, please join our Discord server