How to Use the Flowcode MCP in Google ADK
Feed real-world scan analytics directly into your Google ADK enterprise pipelines and BigQuery datasets.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Flowcode MCP to Google ADK
Create your Vinkius account to connect Flowcode 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.
Direct BigQuery Ingestion via Google ADK
The `get_recent_scans` tool feeds raw offline engagement logs directly to your enterprise pipeline. Your Gemini agent pulls these logs and pipes them into BigQuery for instant SQL analysis. By combining scan logs with digital ad spend, your agent calculates exact cross-channel performance. It uses `list_conversion_rates` to verify which physical locations drive the highest digital sign-ups.
Deep Context Analytics with this MCP Server
The `get_geographic_analytics` tool collects coordinates from physical scans to help your model analyze geographic trends. This MCP Server processes thousands of scan events at once to spot regional trend shifts. Your agent cross-references this geographic data with demographics from `get_audience_summary`. It writes detailed regional reports without hitting context window limits or losing track of historical trends.
Automated Folder and Asset Organization
The `list_folders` tool lets your agent navigate your asset library to organize physical and digital marketing materials. It groups related assets together to keep your enterprise campaigns clean. Auditing active projects is handled via `list_campaigns` to flag codes that lack active landing pages. It then runs `get_flowcode` to inspect target URLs and ensure zero broken links reach the field.
Set up Flowcode MCP in Google ADK
Prerequisites
- Python 3.10+ installed
-
google-adkpackage (pip install google-adk) - Active Vinkius subscription with a valid endpoint token
- 1
Install Google ADK
Run
pip install google-adkto install the Agent Development Kit. MCP support is included via theMcpToolsetclass. - 2
Connect via SSE transport
Use
McpToolset.from_server()withSseServerParamspointing to your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Create an LlmAgent
Pass the returned
mcp_toolslist directly toLlmAgent(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 Flowcode tools in your ADK agent.
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="Flowcode_agent",
model="gemini-2.0-flash",
instruction="You have access to Flowcode tools via MCP.",
tools=mcp_tools,
) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Flowcode. 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.
Why Choose Vinkius
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
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place for every integration
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Common questions about Flowcode MCP in Google ADK
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