How to Use the Addepar MCP in Google ADK

Q: How do I expose Addepar tools to my Google ADK agent?

You instantiate McpToolset with the server URL and pass it to your LlmAgent tools list. Your agent automatically registers the MCP tools for the Gemini model to call.

Q: Can I limit which Addepar tools my Google ADK agent can access?

Yes, you can use the ADK toolnames filter to restrict access. For example, you can expose only listentities and hide transaction tools if your agent only needs to read client names.

Feed Addepar portfolio data straight to your Gemini models using Google ADK to run deep financial analysis.

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Connect Addepar MCP to Google ADK

Create your Vinkius account to connect Addepar 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 Addepar with Google ADK

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Long-Context Portfolio Analysis via Google ADK

The `get_portfolio_analytics` tool feeds raw performance data directly into your Google ADK agent. This allows your Gemini models to digest years of performance history at once, using their massive context window to spot long-term wealth trends. Your agent executes this tool within your Google Cloud environment, making it easy to cross-reference the output with your existing BigQuery tables. This gives you a direct path from raw portfolio metrics to enterprise-grade financial reports.

Automated Position Tracking with Google ADK

The `get_position_details` tool retrieves current holdings and asset allocations for any account in your system. Your Google ADK agent calls this tool to compare current asset weights against target allocations. By combining this MCP Server with Vertex AI, your agent can write back allocation summaries directly to your cloud storage. You get automated tracking of complex portfolios without writing custom API integration code.

Transaction Reconciliation inside Google Cloud

The `list_transactions` tool extracts historical investment activities and cash flows for your Google ADK pipelines. Your agent reads these transactions to build custom timeline visualizations or feed downstream machine learning models. Because the MCP toolset integrates directly with Google Cloud infrastructure, you can restrict access to specific transaction tools using standard ADK filters. This ensures your agent only reads the financial data it needs for the current task.

Setup guide

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

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Common questions about Addepar MCP in Google ADK

You instantiate `McpToolset` with the server URL and pass it to your `LlmAgent` tools list. Your agent automatically registers the MCP tools for the Gemini model to call.

Yes, you can use the ADK tool_names filter to restrict access. For example, you can expose only `list_entities` and hide transaction tools if your agent only needs to read client names.

The ADK handles the data transfer via standard HTTP transport. Gemini models then use their long-context window to analyze the entire payload from `get_position_details` without hitting token limits.

Yes, you can run the MCP Server locally using standard stdio transport or connect to our hosted endpoint. The Google ADK agent communicates with either setup using the same configuration parameters.

The server runs inside an isolated, zero-trust sandbox that handles all authentication tokens securely. Your sensitive client details and account hierarchies are never logged or exposed to the public internet.

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