How to Use the InvestorLift MCP in Google ADK

Q: How do I connect InvestorLift to my Google ADK agent?

Use the McpToolset class with your endpoint configuration. Pass this toolset into the LlmAgent constructor to give your Gemini models direct access to the real estate data.

Q: Can I filter which InvestorLift tools my Google ADK agent sees?

You can. Use the toolnames filter when setting up your McpToolset. This restricts the agent to only the specific functions you want it to perform.

Scale your Google ADK agent operations by connecting directly to InvestorLift data for real-time real estate sourcing.

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Connect InvestorLift MCP to Google ADK

Create your Vinkius account to connect InvestorLift 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 InvestorLift with Google ADK

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Query InvestorLift deals in Google ADK

Connect your Gemini-powered agent to the marketplace using `list_deals`. You can now pull live property data into your existing Google Cloud infrastructure. Your agent parses this data alongside your BigQuery datasets. It makes decisions based on the full scope of your internal and external information.

Manage criteria via Google ADK tools

Use `get_buy_box` to pull your current investment requirements into the agent's memory. If your team updates your strategy in the cloud, use `update_buy_box` to sync the change instantly. This keeps your agent's logic consistent with your evolving acquisition targets. It eliminates the need for manual configuration updates.

Execute messaging from Google ADK

Trigger `send_message` directly from your agent's execution loop. Your agent identifies the seller, constructs the message, and pushes it to the platform. You retain control over the message content while the agent handles the manual delivery. It turns a time-consuming task into a background process.

Setup guide

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

Use the `McpToolset` class with your endpoint configuration. Pass this toolset into the `LlmAgent` constructor to give your Gemini models direct access to the real estate data.

Vinkius handles the underlying authentication. You just provide the endpoint token to the server parameters, and your agent gains authorized access to your marketplace deals.

Your deal information stays within the Vinkius ephemeral sandbox. The server acts as a secure bridge, ensuring no data persists beyond the active agent session.

You can. Use the `tool_names` filter when setting up your `McpToolset`. This restricts the agent to only the specific functions you want it to perform.

The server provides a stable interface for deal fetching. Because Google ADK relies on structured responses, your code remains functional even if the underlying platform data format shifts.

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