How to Use the Uselessfacts MCP in Google ADK

Q: If I need English and German facts, which tools work with Uselessfacts using Google ADK?

Both getrandomfact and gettodayfact support language specification. You just pass 'en' or 'de' to the respective function call.

Inject Fun Context into Enterprise Agents with Uselessfacts | Google ADK

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Connect Uselessfacts MCP to Google ADK

Create your Vinkius account to connect Uselessfacts 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 Uselessfacts with Google ADK

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Perplexity

Retrieve Facts by ID using `get_fact`

The `get_fact(id)` tool lets your LlmAgent pull a specific trivia fact given an ID. This means you can ground complex reasoning with precise, external data points. This works great when your agent needs to reference a fixed piece of knowledge without relying on its training set.

Get Random Facts for Contextualizing Data

You can call `get_random_fact()` and optionally specify the language ('en' or 'de'). This provides context that your agent can use to better interpret data loaded from BigQuery. It’s an easy way to inject varied, non-critical information into a long-context reasoning chain.

Identify Today’s Fact with `get_today_fact`

The `get_today_fact()` tool gives you the daily useless fact. You pass 'en' or 'de' for language control. This is a simple, structured way to ensure your agent always has access to timely, specific data without needing complex date lookups.

Setup guide

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

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Common questions about Uselessfacts MCP in Google ADK

Your LlmAgent treats the MCP Server as a simple toolset. You call the function, and the resulting fact string gets passed directly into your prompt context for reasoning.

While it doesn't check BQ schemas, you can pull a random fact first, and then ask the Gemini model to compare that fact against structured data records. It’s great for illustrative examples.

Because the facts are short, they take up very little of your 1M+ token context window. The data adds flavor without consuming critical reasoning space.

Both `get_random_fact` and `get_today_fact` support language specification. You just pass 'en' or 'de' to the respective function call.

The server only touches fact strings and IDs (integers). This is non-sensitive, public trivia that your agent reads into memory for processing.

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