How to Use the ArborNote MCP in Google ADK

Q: How do I fetch ArborNote clients using Google ADK?

You invoke listarbornoteclients within your toolset. The agent receives the JSON response and parses it for your specific needs.

Q: Can I use ArborNote metrics in my Google ADK pipeline?

Absolutely. You can pipe the output of getarbornotemetrics into your Vertex AI processes for further analysis.

Connect ArborNote to Google ADK. High-context forestry agents for your BigQuery and Vertex AI workflows.

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Connect ArborNote MCP to Google ADK

Create your Vinkius account to connect ArborNote 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 ArborNote with Google ADK

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Link Google ADK to forestry data

Deploy this MCP server to give your Gemini models direct access to `get_arbornote_project` and `get_arbornote_proposal`. It bridges the gap between your cloud infrastructure and your field notes. Long-context reasoning is where this shines. You feed the agent massive amounts of project history, and it makes sense of the details.

Filter tools for Google ADK

Restrict your agent's reach by defining a tool_names filter. You keep the agent focused on specific tasks like checking connectivity with `check_api_health`. This keeps your environment clean. Only the tools you designate get exposed to the LLM.

Query field proposals at scale

Call `list_arbornote_proposals` to pull all active bids into your agent's context. It makes comparing historical data against new requirements trivial. Google ADK manages the transport layer for you. Whether you use stdio or HTTP, the connection remains stable.

Setup guide

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

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Common questions about ArborNote MCP in Google ADK

It works natively. You wrap the server in the McpToolset and your agent gains immediate visibility into your forestry data.

You invoke `list_arbornote_clients` within your toolset. The agent receives the JSON response and parses it for your specific needs.

Absolutely. You can pipe the output of `get_arbornote_metrics` into your Vertex AI processes for further analysis.

It is straightforward. Install the adk package, point it to the endpoint, and define your toolset.

We use a zero-trust architecture. Your assessment files stay behind your private endpoint token and never touch external logs.

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

Mastra AI sdk-typescript

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