How to Use the Gladia (Speech AI) MCP in Google ADK

Q: Is live transcription available for Gladia (Speech AI) in Google ADK?

It is. You invoke initlivesession to start the stream. Your Google ADK agent can then process the incoming text to make immediate decisions.

Q: How do I filter which tools my Google ADK agent can use?

You can use the toolnames filter during setup to restrict the agent. This lets you limit access to only the specific transcription tools you need.

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Connect Gladia (Speech AI) MCP to Google ADK

Create your Vinkius account to connect Gladia (Speech AI) 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 Gladia (Speech AI) with Google ADK

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Perplexity

Batch processing for Google ADK workflows

Start massive transcription jobs using `init_transcription` after you `upload_audio_file` to the server. It fits perfectly into your existing data ingestion pipelines on Google Cloud. Your agent can monitor these jobs by calling `get_transcription` periodically. It keeps your infrastructure load predictable while the server processes your audio files.

Live streaming capabilities for Google ADK

Initialize a live session with `init_live_session` to get instant text feedback on incoming audio streams. It allows your agent to perform real-time analysis on customer calls. This setup works alongside your existing Vertex AI services. Your agent gets a clean stream of text while you maintain full control over the audio input source.

Organize transcriptions with Google ADK

Use `list_transcriptions` to retrieve a history of all your processed audio tasks. It helps you manage your data usage and track which files have been handled. Cleaning up your logs is simple with `delete_transcription`. You can automate this as part of your agent's cleanup routine to keep your project environment organized.

Setup guide

Set up Gladia (Speech AI) 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 Gladia (Speech AI) 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="Gladia (Speech AI)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Gladia (Speech AI) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Gladia (Speech AI) MCP in Google ADK

You integrate the server using the McpToolset provided by the framework. Once connected, your Google ADK agent can call any of the six transcription tools.

Your agent uploads the audio file and triggers a job, then waits for the result. The text output flows straight into your agent's reasoning process.

It is. You invoke `init_live_session` to start the stream. Your Google ADK agent can then process the incoming text to make immediate decisions.

You can use the tool_names filter during setup to restrict the agent. This lets you limit access to only the specific transcription tools you need.

The server treats your audio as transient data. Once the transcription task finishes, the system handles the data according to your specified retention settings.

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