How to Use the Pennylane MCP in Google ADK

Q: Can I use Google ADK to run bulk Pennylane reports?

Yes, you can pull massive datasets using listcustomerinvoices and pass them to Google ADK. The long-context window of Gemini models allows your agent to analyze thousands of accounting rows at once.

Q: How do I connect my Pennylane MCP Server to Google ADK?

You initialize the McpToolset with the Vinkius HTTP transport URL. Pass this toolset directly to your LlmAgent in Python, and Google ADK will expose the tools to your Gemini model.

Q: Can Google ADK agents create new clients in Pennylane?

Yes, your agent can use createcustomer to register clients automatically. You can restrict this tool inside your Google ADK toolset parameters if you want to limit the agent to read-only operations.

Feed Pennylane accounting data directly into Google ADK to run long-context financial analysis across 1M tokens of ledger history.

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Connect Pennylane MCP to Google ADK

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Setup Pennylane with Google ADK

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Sync Pennylane data to Google ADK

The MCP Server exposes `list_customer_invoices` to retrieve your entire billing history so your Google ADK agent can map it against BigQuery datasets. This lets your Google ADK agent run predictive cash flow models using real-time Pennylane records.

Audit suppliers via Google ADK MCP Server

`list_suppliers` exposes your vendor directory to Google ADK for automated Pennylane compliance checks. The Google ADK agent cross-references supplier details from `get_supplier_details` with corporate registries stored in Google Cloud Storage.

Classify products with Google ADK

`list_products` grabs your current catalog so Google ADK can organize your Pennylane tax categories. The Google ADK agent reads the list, checks the French Plan Comptable Général via `list_categories`, and suggests the correct Pennylane accounting codes.

Setup guide

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

Yes, you can pull massive datasets using `list_customer_invoices` and pass them to Google ADK. The long-context window of Gemini models allows your agent to analyze thousands of accounting rows at once.

You initialize the `McpToolset` with the Vinkius HTTP transport URL. Pass this toolset directly to your `LlmAgent` in Python, and Google ADK will expose the tools to your Gemini model.

Yes, your agent can use `create_customer` to register clients automatically. You can restrict this tool inside your Google ADK toolset parameters if you want to limit the agent to read-only operations.

The framework manages execution queues when fetching large lists like `list_estimates`. If Pennylane rate limits the agent, Google ADK pauses and retries the request using backoff logic.

All MCP queries pass through secure HTTPS tunnels directly to your Google Cloud environment. No financial data is cached or stored in the Vinkius sandbox, keeping your French tax records completely private.

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