How to Use the Griffin MCP in Google ADK

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

You can. Use a toolnames filter during initialization to restrict the agent, ensuring it only uses specific functions like listpayees or gettransaction.

Connect Griffin to your Google ADK infrastructure. Use Gemini's long-context reasoning for complex fintech data analysis.

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Connect Griffin MCP to Google ADK

Create your Vinkius account to connect Griffin 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 Griffin with Google ADK

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Perplexity

Scale banking operations with Google ADK

Your agent acts on live account data by calling `get_account` and `list_accounts`. Since you already use Google Cloud, this integration lets your agents reason over large datasets without moving files. Gemini models process these inputs to identify patterns or anomalies. You get a direct pipeline from your banking resources into your existing BigQuery-backed workflows.

Manage complex organization structures

Use `list_organizations` to map out your entity hierarchy. This allows your agent to switch contexts between different business units instantly when performing transfers or status checks. Every tool call is routed through the ADK, keeping your infrastructure clean. You can restrict which tools are available to specific agents, ensuring they only touch the data they need.

Streamline KYC with long-context reasoning

The Griffin server provides deep visibility into verifications through `list_verifications`. Because Gemini handles 1M+ tokens, your agent can analyze entire histories to spot compliance gaps. It performs these checks autonomously. You define the logic, and the agent executes the necessary calls to verify identity or business status across your entire organization.

Setup guide

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

You instantiate an McpToolset using the Vinkius endpoint. The ADK then registers the Griffin tools natively, allowing your agent to call them as standard functions.

You can. Use a tool_names filter during initialization to restrict the agent, ensuring it only uses specific functions like `list_payees` or `get_transaction`.

It does. You choose the transport that fits your deployment, whether you're running locally in a terminal or inside a cloud-based agent pipeline.

The connection is optimized for low-overhead communication. By using the streamable HTTP transport, your agent interacts with the bank ledger with minimal delay.

Data remains inside the Vinkius-managed sandbox during the session. The Griffin server never stores your sensitive verification records; it simply passes the necessary data to your agent's memory.

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