How to Use the Brex MCP in Google ADK

Q: Can I use Google ADK to fetch Brex vendor lists?

Yes, the brexlistvendors tool is available for your agent to query your saved AP vendors. This is useful for verifying payment details before initiating a transfer.

Sync your Google ADK agent with Brex to automate corporate payments and card issuance.

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Connect Brex MCP to Google ADK

Create your Vinkius account to connect Brex 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 Brex with Google ADK

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Route employees through Google ADK

The `brex_create_user` tool allows your agent to onboard new team members to your Brex account instantly. It takes the email and name inputs directly from your existing directory logic. Running this inside your Google ADK agent means you can trigger onboarding as part of a larger employee setup workflow. It keeps your team permissions in sync with your corporate spending platform.

Analyze budgets in Google ADK

Query your team's budget programs using `brex_list_budgets` to get a clear view of spend caps. Your agent can compare these figures against your current cash balance from `brex_get_balance`. This gives your Google ADK agent the context needed to approve or deny expenses automatically. It brings your financial data into the same environment as your vertex-based reasoning models.

Sweep transactions with Google ADK

Your agent uses `brex_list_transactions` to pull historical data into your local analysis tools. It gathers card and account records for audit or reporting purposes. Once the data is inside your Google ADK environment, you can process it alongside your other cloud infrastructure logs. It provides a direct line to your financial history without manual exports.

Setup guide

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

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Common questions about Brex MCP in Google ADK

You initialize the McpToolset with the server URL and pass it into your agent's tool list. This allows the agent to interact with Brex functions through the standard framework interface.

No, the server handles authentication via a single endpoint token. Your agent never sees or stores your actual login details, keeping your access keys private.

Yes, the `brex_list_vendors` tool is available for your agent to query your saved AP vendors. This is useful for verifying payment details before initiating a transfer.

Your financial data, including transaction amounts and vendor names, is processed in a memory-safe sandbox. It is never exposed to public models or unauthorized endpoints.

Because the agent handles the MCP stream, it can process large lists of transactions or users efficiently. It is designed to work with the long-context capabilities of your Gemini models.

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