How to Use the PHC GO MCP in Google ADK

Q: How does the Google ADK handle large product catalogs from PHC GO?

Gemini's long context easily manages large outputs from listproducts. The Google ADK handles the data transfer efficiently, allowing the model to search through thousands of items without hitting context limits.

Feed live PHC GO ERP data straight into Gemini models using the Google ADK and our hosted MCP Server.

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Connect PHC GO MCP to Google ADK

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Setup PHC GO with Google ADK

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Connect BigQuery and PHC GO with Google ADK

Bring your ERP data into your Google Cloud ecosystem. The Google ADK lets your Gemini models query live stock levels using `list_stocks` and match them against historical sales data stored in BigQuery. This integration allows your agent to cross-reference customer profiles using `get_customer_details` before running machine learning predictions. You get a direct loop between your cloud database and your active ERP.

Long-context reasoning over ERP documents

Gemini models handle massive context windows, making them perfect for analyzing long transaction histories. Pass thousands of invoice lines retrieved via `list_documents` directly into your Google ADK agent. The agent can review weeks of billing history using `list_current_accounts` to find discrepancies. It processes this data in a single run without losing track of important details or needing complex chunking strategies.

Enterprise-grade MCP Server tool filtering

Keep your ERP secure by exposing only the tools your agent actually needs. The Google ADK lets you define a strict tool_names list when initializing the McpToolset for your ERP. You can restrict a customer-facing agent to `search_customers` and `get_product_details` while completely hiding write operations. This ensures your live inventory and billing records remain untouched by unauthorized LLM calls.

Setup guide

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

Use the McpToolset class with StreamableHttpServerParameters pointing to your Vinkius URL. Pass this toolset to your LlmAgent to instantly expose tools like `list_warehouses` and `list_taxes` to Gemini.

Yes, if you grant permission, the model can execute write tools. It can run `create_customer` or `create_product` based on data extracted from emails or documents processed in Google Cloud.

Gemini's long context easily manages large outputs from `list_products`. The Google ADK handles the data transfer efficiently, allowing the model to search through thousands of items without hitting context limits.

Yes, the server supports both HTTP and Stdio transports. You can run your Google ADK agent locally for development or deploy it to Vertex AI using the same secure Vinkius endpoint.

Yes, all stock movements and catalog metadata retrieved via `list_stocks` pass through secure, encrypted channels. Google Cloud instances access the Vinkius V8 sandbox using ephemeral tokens, ensuring no ERP records are cached or exposed.

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