How to Use the DocsGenFlow MCP in Google ADK

Q: Can Gemini models use DocsGenFlow and Google ADK to update templates?

Yes, your Google ADK agent calls createtemplate to define new layouts dynamically. This allows your agent to adapt document designs based on real-time feedback from your database.

Q: How do we monitor DocsGenFlow history in Google ADK?

Your agent queries listhistory to get a complete log of all generation events. This metadata helps your cloud functions track usage and detect anomalies in real time.

Generate enterprise-grade documents from BigQuery data using Google ADK and Gemini long-context models connected to your DocsGenFlow MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect DocsGenFlow MCP to Google ADK

Create your Vinkius account to connect DocsGenFlow 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.

GDPR Free for Subscribers

Setup DocsGenFlow with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Native BigQuery to Document Pipelines

`generate_document` processes your massive cloud datasets directly into clean, structured files. Your Gemini agent reads rows from BigQuery, formats the fields, and feeds them straight into this tool. Run `check_docsgenflow_status` first to check if the MCP connection is ready for high-volume execution. This keeps your automated cloud workflows reliable and prevents data processing bottlenecks.

Context-Aware Template Selection using Google ADK

`list_templates` allows your long-context Gemini model to scan all available layouts in a single turn. The agent matches user requirements to the correct template structure without needing hardcoded routing rules. Use `get_template` to inspect the exact merge fields required for your chosen layout. Your agent checks that the BigQuery payload matches the template schema before initiating the generation.

Enterprise Lifecycle Management

`list_documents` lets your agent audit all previously generated files directly from your cloud console. This is crucial for checking that automated batch jobs completed without errors. Your agent invokes `download_document` to move files from the MCP tool storage into your Google Cloud Storage buckets. This ensures your team maintains a secure, centralized archive of all customer communications.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DocsGenFlow. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect DocsGenFlow now

Real-time monitoring

Live

visibility into every interaction

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.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about DocsGenFlow MCP in Google ADK

Import McpToolset and pass your Vinkius HTTP transport URL to the StreamableHttpServerParameters configuration. Add the toolset to your LlmAgent constructor to expose all ten MCP tools.

Yes, your Google ADK agent calls `create_template` to define new layouts dynamically. This allows your agent to adapt document designs based on real-time feedback from your database.

Your agent queries `list_history` to get a complete log of all generation events. This metadata helps your cloud functions track usage and detect anomalies in real time.

Yes, the HTTP transport connects securely through our managed gateway. This setup allows your agent to communicate with the server without exposing internal infrastructure.

Your files remain in our secure storage until your agent calls `download_document` to pull them. We encrypt all template designs and document outputs at rest using AES-256 keys.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript