How to Use the Aidbase MCP in Google ADK

Q: Which method restricts Google ADK agents from modifying this Aidbase MCP Server setup?

Use the toolnames filter when initializing your McpToolset in Python. This ensures your public-facing Gemini models can only read data, while administrative tools remain locked behind your backend service accounts.

Q: What is the fastest way to check if my support endpoints are online?

Run checkaidbasestatus at the start of your cloud function pipeline. This lightweight tool returns a quick health check, letting you pause automated workflows if the main API goes offline.

Link your Google ADK pipelines to this Aidbase MCP Server to feed BigQuery data directly into support workflows.

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Connect Aidbase MCP to Google ADK

Create your Vinkius account to connect Aidbase 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 Aidbase with Google ADK

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Run high-volume support checks with this Google ADK MCP Server tool

`list_aidbase_inboxes` exposes all your active email support channels to Gemini's massive context window. Your Google ADK agent pulls this list to map incoming customer queries to the correct department inbox, processing thousands of emails in a single reasoning loop. Because Gemini handles over a million tokens, you can feed entire support histories directly alongside these Aidbase inbox configurations. This Google ADK architecture lets you spot repeating support trends without writing custom data pipelines.

Inject enterprise knowledge bases on the fly

`add_aidbase_faq_item` writes verified answers directly into your support repository based on real-time data. Your Google ADK agent parses fresh product updates from Google Cloud Storage and updates your public FAQs instantly. This automated Google Cloud pipeline ensures your customer-facing Aidbase bots always have access to the latest product specifications. You eliminate the lag between engineering releases and Gemini-powered customer support updates.

Query active chatbot configurations

`get_aidbase_chatbot` retrieves the exact system prompt and settings for any deployed support widget. Your Google ADK agent compares these settings against your enterprise compliance guidelines stored in BigQuery, flagging any deviations. This continuous audit loop runs headless in your Google Cloud environment to monitor Aidbase widgets. You get immediate alerts if a chatbot's configuration drifts from your approved Gemini safety templates.

Setup guide

Set up Aidbase 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 Aidbase 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="Aidbase_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Aidbase 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 Aidbase. 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 Aidbase MCP in Google ADK

You pass your Vinkius endpoint token into the StreamableHttpServerParameters constructor. The ADK establishes a secure HTTP transport layer that lets Gemini execute tools like list_aidbase_knowledge securely.

Absolutely, you can feed large documents to Gemini and have it call add_aidbase_faq_item repeatedly within a single execution block. The ADK manages the tool execution queue to prevent rate-limiting issues on your support dashboard.

Use the tool_names filter when initializing your McpToolset in Python. This ensures your public-facing Gemini models can only read data, while administrative tools remain locked behind your backend service accounts.

Run check_aidbase_status at the start of your cloud function pipeline. This lightweight tool returns a quick health check, letting you pause automated workflows if the main API goes offline.

Your data travels through an ephemeral, end-to-end encrypted channel that bypasses persistent storage entirely. Vinkius isolates each execution in a secure virtual container, ensuring your internal documentation URLs are never cached or exposed to external networks.

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