How to Use the ElevenLabs MCP in Google ADK

Q: Where do I find my ElevenLabs voice IDs for Google ADK?

Simply trigger listvoices from your agent. It will return a list of every voice available to your account, including IDs and metadata for each one.

Q: Is it possible to cache audio to save costs?

You can use listhistory to check if a specific phrase has already been generated. If it exists, retrieve the file instead of burning characters on a fresh request.

Connect ElevenLabs to your Google ADK agent to power enterprise-grade voice output within your Google Cloud infrastructure.

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Connect ElevenLabs MCP to Google ADK

Create your Vinkius account to connect ElevenLabs to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup ElevenLabs with Google ADK

Ask AI about this MCP

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Claude

Perplexity

High-speed text-to-speech for Google ADK

Convert your processed data into audio using `text_to_speech`. This allows your agent to bridge the gap between BigQuery analytics and human-readable output. Check `list_models` to pick the right engine for your specific Google Cloud workload. You decide if you need raw speed or maximum expressive range.

Granular voice control

Use `list_voices` to browse the full library and `get_voice` to pull detailed parameters for a specific speaker. This makes it easy to swap voices based on the user's context. You avoid manual configuration by letting the agent query these settings directly. It ensures your application stays modular and easy to update.

Usage visibility for enterprise agents

Keep your project managers happy by calling `get_subscription` to track character consumption across your agent fleet. It prevents unexpected overages in high-volume environments. Use `list_projects` to organize your dubbing tasks into logical buckets. This keeps your agent's interactions organized and audit-ready.

Setup guide

Set up ElevenLabs MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with ElevenLabs tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="ElevenLabs_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ElevenLabs tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ElevenLabs. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about ElevenLabs MCP in Google ADK

You instantiate the MCP server as a toolset within your agent definition. Once connected, your agent treats ElevenLabs functions like any other native library call.

Yes. Your agent can query your database, format the result into a string, and pass it to `text_to_speech`. It turns raw data into an immediate, spoken answer.

Simply trigger `list_voices` from your agent. It will return a list of every voice available to your account, including IDs and metadata for each one.

You can use `list_history` to check if a specific phrase has already been generated. If it exists, retrieve the file instead of burning characters on a fresh request.

The MCP server acts as a gateway that only exposes the tools you explicitly call. Your ElevenLabs credentials are never stored in your agent code, and all data exchange occurs over encrypted channels.

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