How to Use the Gingr MCP in Google ADK

Q: How do I load Gingr tools into my Google ADK environment?

Install the google-adk library and initialize the McpToolset with your Vinkius HTTP transport URL. Pass the toolset object directly into your LlmAgent constructor to expose the tools to Gemini.

Q: Can I restrict which Gingr tools my Google ADK agent can execute?

Yes, you can use the toolnames filter parameter when configuring your McpToolset in Python. This limits your Google ADK agent to specific tasks, such as only allowing it to run findownerbyemail while blocking reservation lookups.

Q: How does the Gingr MCP Server handle high-volume data searches in Google ADK?

The findownerbyphone tool executes targeted queries to retrieve specific customer files instantly. This avoids pulling massive datasets into Google ADK, keeping your token usage low and your agent responses fast.

Q: How do I test the connection between Google ADK and my kennel database?

You'll run the verifyapiconnection tool directly through your Python agent script. This executes a fast HEAD request to check your credentials before the agent attempts to pull active check-in sheets.

Q: Where is my custom pet medical data stored and processed?

Custom pet medical records retrieved by searchpetcustomfields are processed in ephemeral MCP Server sandboxes. The Google ADK receives this data over an encrypted HTTP connection, and no pet health records are stored permanently on Vinkius servers.

Feed real-time pet care data directly into your Google ADK pipelines for enterprise-grade kennel logistics and analytics.

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Connect Gingr MCP to Google ADK

Create your Vinkius account to connect Gingr 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 Gingr with Google ADK

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Analyze boarding trends with Gemini and Google ADK

The `list_owner_reservations` tool extracts historical and upcoming booking records directly into your Google ADK context window. Gemini's million-token context window allows your agent to analyze years of reservation history in a single prompt. By routing this data through our MCP Server, you can forecast seasonal boarding rushes right inside your enterprise pipeline. Your agents get immediate access to booking trends without manual CSV exports.

Monitor kennel occupancy through Google Cloud agents

The `get_digital_whiteboard` tool exposes your current kennel layout and dog placements to Google ADK agents. Your agents parse this digital board to help staff optimize run assignments and prevent dangerous dog-on-dog interactions. This integration routes real-time physical occupancy data directly into Vertex AI. Your staff get instant, automated recommendations on where to place incoming pets during peak morning drop-off hours.

Query custom owner files using this MCP Server

The `search_owner_custom_fields` tool allows Google ADK agents to scan specialized customer notes and loyalty preferences. Your agent uses this custom data to personalize SMS templates or email outreach programs. Because Google ADK supports direct tool filtering, you can restrict your agent's access to specific fields. This ensures your AI client only reads the exact customer parameters required for the active task.

Setup guide

Set up Gingr 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 Gingr 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="Gingr_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Gingr tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Gingr MCP in Google ADK

Install the `google-adk` library and initialize the `McpToolset` with your Vinkius HTTP transport URL. Pass the toolset object directly into your `LlmAgent` constructor to expose the tools to Gemini.

Yes, you can use the `tool_names` filter parameter when configuring your `McpToolset` in Python. This limits your Google ADK agent to specific tasks, such as only allowing it to run `find_owner_by_email` while blocking reservation lookups.

The `find_owner_by_phone` tool executes targeted queries to retrieve specific customer files instantly. This avoids pulling massive datasets into Google ADK, keeping your token usage low and your agent responses fast.

You'll run the `verify_api_connection` tool directly through your Python agent script. This executes a fast HEAD request to check your credentials before the agent attempts to pull active check-in sheets.

Custom pet medical records retrieved by `search_pet_custom_fields` are processed in ephemeral MCP Server sandboxes. The Google ADK receives this data over an encrypted HTTP connection, and no pet health records are stored permanently on Vinkius servers.

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