How to Use the Faker MCP in Google ADK

Q: How do I restrict the Faker tools exposed to Google ADK?

Use the toolnames filter when initializing the McpToolset. This lets you choose exactly which generators are available to the agent.

Feed your Google ADK agents with generated mock data on the fly.

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Connect Faker MCP to Google ADK

Create your Vinkius account to connect Faker 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 Faker with Google ADK

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Integrate Faker tools into Google ADK

Load the toolset directly into your LlmAgent using the McpToolset class. Whether you need `get_books` or `get_places`, the integration maps them to your agent's capability set immediately. This allows your Gemini-powered agents to reason over mock datasets. You can now build workflows that interact with synthetic data as if it were coming from your BigQuery tables.

Use Faker for enterprise agent development

Populate your agent's context window using `get_texts` or `get_users` to test long-context reasoning. You can feed massive mock datasets into Gemini models to see how they perform under load. It works with your existing Google Cloud infrastructure. You can restrict tool access using the name filter, ensuring the agent only uses the specific data generators you permit.

Deploy this MCP Server for testing workflows

Your agent can now pull mock data from this MCP Server to validate internal processing logic. It supports both Stdio and HTTP transports, so it fits into any Google Cloud deployment. This ensures your agent is ready for production without using live data. You get the benefit of testing against high-quality mocks while maintaining your security standards.

Setup guide

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

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Common questions about Faker MCP in Google ADK

Use the tool_names filter when initializing the McpToolset. This lets you choose exactly which generators are available to the agent.

The server supports localization parameters. You can request addresses or company names specific to different regions, which your agent will receive as standard JSON.

Absolutely. Since the agent framework handles the protocol, the Gemini model receives the tool outputs as structured text it can process naturally.

You only need your Vinkius endpoint token. The SDK handles the connection details once you provide the server URL and your auth credentials.

The server generates ephemeral mock data. It does not persist any information, ensuring that your sensitive enterprise data stays within your controlled Google Cloud infrastructure.

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