Skip to main content
Glama
elevenlabs

ElevenLabs MCP Server

Official
by elevenlabs

create_agent

Build a custom conversational AI agent by configuring voice, language, system prompt, and model settings for personalized interactions.

Instructions

Create a conversational AI agent with custom configuration.

⚠️ COST WARNING: This tool makes an API call to ElevenLabs which may incur costs. Only use when explicitly requested by the user.

Args:
    name: Name of the agent
    first_message: First message the agent will say i.e. "Hi, how can I help you today?"
    system_prompt: System prompt for the agent
    voice_id: ID of the voice to use for the agent
    language: ISO 639-1 language code for the agent
    llm: LLM to use for the agent
    temperature: Temperature for the agent. The lower the temperature, the more deterministic the agent's responses will be. Range is 0 to 1.
    max_tokens: Maximum number of tokens to generate.
    asr_quality: Quality of the ASR. `high` or `low`.
    model_id: ID of the ElevenLabs model to use for the agent.
    optimize_streaming_latency: Optimize streaming latency. Range is 0 to 4.
    stability: Stability for the agent. Range is 0 to 1.
    similarity_boost: Similarity boost for the agent. Range is 0 to 1.
    turn_timeout: Timeout for the agent to respond in seconds. Defaults to 7 seconds.
    max_duration_seconds: Maximum duration of a conversation in seconds. Defaults to 600 seconds (10 minutes).
    record_voice: Whether to record the agent's voice.
    retention_days: Number of days to retain the agent's data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
first_messageYes
system_promptYes
voice_idNocgSgspJ2msm6clMCkdW9
languageNoen
llmNogemini-2.0-flash-001
temperatureNo
max_tokensNo
asr_qualityNohigh
model_idNoeleven_turbo_v2
optimize_streaming_latencyNo
stabilityNo
similarity_boostNo
turn_timeoutNo
max_duration_secondsNo
record_voiceNo
retention_daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes
textYes
annotationsNo
_metaNo
Behavior3/5

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

Annotations already set destructiveHint=false and openWorldHint=true. The description adds that it makes an API call and may incur costs, but does not elaborate on failure modes or side effects beyond creation. Adequate but not exceptional.

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 relatively long due to the parameter list, but it is well-structured with a front-loaded cost warning and a clear 'Args:' section. Every sentence adds value given the tool's complexity.

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 output schema exists, the description does not need to explain return values. It covers creation behavior, parameter constraints, and usage conditions. Missing information about error handling or validation, but overall complete for its purpose.

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?

Schema description coverage is 0%, so the description carries full burden. It provides detailed explanations for all 17 parameters, including defaults, ranges, and meanings (e.g., temperature range, stability range, turn_timeout default). This fully compensates for the missing schema descriptions.

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 'Create a conversational AI agent with custom configuration', which is a specific verb + resource. It distinguishes from siblings like 'add_knowledge_base_to_agent' and 'get_agent' by focusing on creation.

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

Usage Guidelines4/5

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

The description includes a cost warning that tells the agent to only use when explicitly requested by the user, providing a clear usage condition. It does not explicitly mention alternatives, but the warning effectively guides when not to use.

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/elevenlabs/elevenlabs-mcp'

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