How to Use the Hive AI MCP in Google ADK

Q: Can Google ADK agents detect deepfakes using Hive AI?

Yes, your Google ADK agent can call detectaigeneratedimage to identify synthetic media. This allows Gemini to flag potential deepfakes before they are indexed into your Google Cloud databases.

Q: How does Hive AI handle async media jobs in Google ADK?

The Google ADK agent triggers moderatevideoasync or moderateaudioasync to start the background job. It then uses getasynctaskstatus to monitor progress and pulls the results with getasynctaskresult.

Q: How can I verify which models my Google ADK agent can access?

The Google ADK agent can invoke listavailablemodels to inspect your active classification models. You can also retrieve your workspace setup using getprojectdetails directly from Gemini.

Protect your Google ADK enterprise pipelines by connecting Gemini models directly to Hive AI moderation and detection tools.

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Connect Hive AI MCP to Google ADK

Create your Vinkius account to connect Hive 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 Hive AI with Google ADK

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Google ADK Integration with Hive AI MCP Server

These tools integrate directly into your Google ADK enterprise pipelines, allowing your long-context Gemini agents to verify files before storing them in BigQuery. The integration uses the standard streamable HTTP transport to map moderation tools directly into Gemini's function calling layer. Your Google ADK agent can process massive contexts and selectively run `moderate_image` on referenced assets. This keeps your enterprise data clean and ensures that user-provided inputs are safe before they feed into your downstream Vertex AI models.

Filter Synthetic Assets in BigQuery Pipelines

Filter synthetic data from your analytical pipelines using `detect_ai_generated_image` and `detect_ai_generated_text` inside Google ADK. This MCP configuration lets you exclude bot-written comments before they pollute your data warehouse. If a batch of user reviews looks suspicious, your Gemini agent calls `detect_ai_generated_text` to evaluate the content. This prevents bot-generated feedback from skewing your Google ADK business intelligence reports.

Process Bulk Media with Google ADK Async Tasks

Offload large file processing using `moderate_video_async` and `moderate_audio_async` within your Google ADK pipelines. The MCP server provides background processing to prevent Gemini context timeouts when analyzing media files. The Google ADK agent polls the status with `get_async_task_status` and fetches the final JSON payload via `get_async_task_result`. This asynchronous workflow fits perfectly within Google ADK's long-running enterprise execution pipelines.

Setup guide

Set up Hive 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 Hive 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="Hive AI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Hive AI 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 Hive AI. 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.

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Common questions about Hive AI MCP in Google ADK

You instantiate an MCP toolset pointing to the Vinkius HTTP endpoint and pass it to your Google ADK `LlmAgent` tools list. The agent automatically discovers tools like `moderate_text` and makes them available to Gemini.

Yes, your Google ADK agent can call `detect_ai_generated_image` to identify synthetic media. This allows Gemini to flag potential deepfakes before they are indexed into your Google Cloud databases.

The Google ADK agent triggers `moderate_video_async` or `moderate_audio_async` to start the background job. It then uses `get_async_task_status` to monitor progress and pulls the results with `get_async_task_result`.

The Google ADK agent can invoke `list_available_models` to inspect your active classification models. You can also retrieve your workspace setup using `get_project_details` directly from Gemini.

Yes, all images, text, audio, and video content moderation data processed by this server travel through isolated V8 sandboxes. Vinkius secures your Google ADK credentials, and the data is transmitted over encrypted channels to Hive AI for real-time classification.

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