How to Use the Evernest Property Management MCP in Google ADK

Q: How do I register the Evernest Property Management tools with my Google ADK agent?

Use the McpToolset class from the google-adk package, passing the server's streamable HTTP URL. Then, add this toolset to your LlmAgent constructor to expose endpoints like listmanagedproperties.

Q: Can I filter which Evernest Property Management tools are exposed to my Google ADK model?

Yes, you can pass a list of allowed tool names to the McpToolset constructor. This prevents the Google ADK agent from calling sensitive tools like getevernestaccountmetadata if you only want it to manage repairs.

Q: How do I combine Vertex AI pipelines with Evernest property data?

Your Google ADK agent calls quickpropertyportfolioaudit to fetch current operational metrics. You can then pipe this structured JSON payload directly into Vertex AI prediction nodes to forecast vacancy rates across your portfolio.

Q: Is my Evernest lease agreement data safe when processed by Google ADK?

Yes. The server processes all listactiveleaseagreements requests within an isolated, ephemeral V8 container on Vinkius. Your contractual lease agreements and tenant financial terms are encrypted in transit and never cached or stored on external disks.

Connect Gemini to your rental portfolio using Google ADK to analyze tenant history and schedule repairs directly from BigQuery.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Evernest Property Management MCP to Google ADK

Create your Vinkius account to connect Evernest Property Management 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.

GDPR Free for Subscribers

Setup Evernest Property Management with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-Property Financial Auditing via Gemini

The `get_property_detailed_data` tool retrieves financial metrics and specific settings for any property in your Evernest portfolio directly into your Google ADK environment. Gemini models process these raw financial figures alongside your historical datasets stored in BigQuery. By feeding this data into Google ADK, your agent can cross-reference property expenses against local market trends. The long-context window of Gemini handles years of property records and owner statements in a single reasoning loop.

Enterprise Maintenance Tracking with Google ADK

The `list_maintenance_tickets` tool provides your Google ADK agent with a complete log of active and historical repair requests. Your model scans this list to identify recurring issues, like chronic plumbing failures, across hundreds of managed units. Because this MCP Server integrates with Google Cloud, you can export these ticket logs directly into Vertex AI to train custom predictive maintenance models. The agent uses `list_high_priority_repairs` to route critical issues to your field technicians in real time.

Tenant Profile Extraction and Contract Analysis

The `get_tenant_detailed_profile` tool extracts tenant histories and payment records for your Google ADK workflow. Your agent combines this profile data with `list_active_lease_agreements` to flag renters who are approaching their lease end dates or have outstanding balances. This setup allows Gemini to process complex lease contracts without truncating the text. Google ADK manages the raw API responses safely, ensuring your agent has the exact tenant details needed before drafting renewal offers.

Setup guide

Set up Evernest Property Management 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 Evernest Property Management 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="Evernest Property Management_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Evernest Property Management tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Evernest Property Management. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Evernest Property Management now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Evernest Property Management MCP in Google ADK

Use the `McpToolset` class from the `google-adk` package, passing the server's streamable HTTP URL. Then, add this toolset to your `LlmAgent` constructor to expose endpoints like `list_managed_properties`.

Yes, you can pass a list of allowed tool names to the `McpToolset` constructor. This prevents the Google ADK agent from calling sensitive tools like `get_evernest_account_metadata` if you only want it to manage repairs.

Yes, you can run this MCP Server using either the standard Stdio transport or Streamable HTTP. Google ADK handles both protocols, allowing you to run your agent locally or host it on Google Cloud Run.

Your Google ADK agent calls `quick_property_portfolio_audit` to fetch current operational metrics. You can then pipe this structured JSON payload directly into Vertex AI prediction nodes to forecast vacancy rates across your portfolio.

Yes. The server processes all `list_active_lease_agreements` requests within an isolated, ephemeral V8 container on Vinkius. Your contractual lease agreements and tenant financial terms are encrypted in transit and never cached or stored on external disks.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript