How to Use the Math Evaluation Engine MCP in Google ADK

Q: How do I connect the Math Evaluation Engine to the Google ADK?

Install google-adk. Create an McpToolset pointing to your server URL. Pass it to your LlmAgent initialization under the tools parameter.

Q: Can I restrict which Math Evaluation Engine tools my Google ADK agent sees?

You can apply the toolnames filter in the ADK. This lets you expose only the rounding tool while hiding the expression calculator if needed.

Force Gemini to do exact math. Connect the Math Evaluation Engine MCP Server to your Google ADK pipelines.

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Connect Math Evaluation Engine MCP to Google ADK

Create your Vinkius account to connect Math Evaluation Engine 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 Math Evaluation Engine with Google ADK

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BigQuery Arithmetic via Google ADK

The `calculate_expression` tool intercepts raw math tasks before Gemini attempts to solve them natively. When your agent pulls a million rows of financial data from BigQuery, it hands the aggregation formulas to this engine. The mathjs parser evaluates the string and returns the exact number. Gemini's massive context window is great for reading data, but terrible at calculating it. Offloading the actual arithmetic to an external MCP Server keeps your Google Cloud pipelines strictly deterministic.

Precision Rounding for Vertex AI

The `round_value` tool forces floating-point numbers into exact decimal constraints. Your agent passes a messy float generated from a Vertex AI predictive model, and this tool truncates it cleanly. You need exact penny-matching when pushing data back into enterprise systems. This tool guarantees the final output matches legacy decimal-based formatting rules, bypassing the standard IEEE 754 representation errors.

Native Toolset Registration

Both `calculate_expression` and `round_value` load directly into your Gemini agent using the `McpToolset` class. You pass the `StreamableHttpServerParameters` with your Vinkius URL, and the Google ADK handles the transport layer. You can also apply the `tool_names` filter to restrict exposed tools if you only want the agent to access rounding functions. The integration fits right into your existing Google Cloud Python infrastructure.

Setup guide

Set up Math Evaluation Engine 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 Math Evaluation Engine 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="Math Evaluation Engine_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Math Evaluation Engine tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Math Evaluation Engine MCP in Google ADK

Install `google-adk`. Create an `McpToolset` pointing to your server URL. Pass it to your `LlmAgent` initialization under the `tools` parameter.

Yes. It stops Gemini from guessing the results of complex queries. The agent builds the formula string, and the engine computes the exact answer.

You can apply the `tool_names` filter in the ADK. This lets you expose only the rounding tool while hiding the expression calculator if needed.

The engine executes mathjs operations in under 10ms. Your agent gets the deterministic result almost instantly without blocking the main event loop.

The server only receives isolated mathematical strings and float values. The zero-trust architecture ensures every calculation runs in a completely isolated memory space that terminates immediately after returning the result. No logs are retained.

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