How to Use the Kissflow MCP in Google ADK

Q: How does the Google ADK handle Kissflow dataform entries?

The agent calls listdataforms to identify the correct container, then uses listdataformitems to pull the raw form submissions for your analysis.

Give your Google ADK agents direct access to Kissflow datasets and workflows on Gemini's long-context window.

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Connect Kissflow MCP to Google ADK

Create your Vinkius account to connect Kissflow 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 Kissflow with Google ADK

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Context-aware process automation

Gemini models excel at processing massive contexts from Kissflow workflows. By feeding Kissflow data into your Google ADK agent using this MCP Server, you let it analyze long histories of business requests using `list_process_items` and `list_processes` without losing the thread. The agent reads entire Kissflow process histories in a single pass. It identifies bottlenecks in your Kissflow approval chains and suggests concrete fixes based on actual operational history.

Expose Kissflow tables to Google ADK

Enterprise data in Kissflow shouldn't live in a silo. This MCP Server lets your agent pull reference tables with `list_datasets` and `list_dataset_items`, making that information instantly available to your Gemini models. You can feed these Kissflow records directly into your BigQuery or Vertex AI pipelines. Your Google ADK agent acts as the bridge, moving master data from your low-code Kissflow apps straight into your cloud analytics.

Audit user access and group memberships

Security audits in Kissflow require mapping users to their respective roles. Your Google ADK agent can call `list_users` and `list_groups` to build a clean directory map of who has access to what in Kissflow. By querying `get_user_details`, the Google ADK agent can flag inactive Kissflow accounts or incorrect group assignments. It keeps your Kissflow user directory clean without forcing you to write manual scripts.

Setup guide

Set up Kissflow 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 Kissflow 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="Kissflow_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kissflow 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 Kissflow. 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.

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Common questions about Kissflow MCP in Google ADK

Instantiate an HTTP toolset pointing to your Vinkius endpoint, then pass that toolset to your LlmAgent constructor. Your Gemini agent will immediately see the Kissflow tools.

Yes. You can use the optional tool name filter in the toolset parameters to expose only specific tools, like `list_datasets`, while hiding administrative tools.

The agent calls `list_dataforms` to identify the correct container, then uses `list_dataform_items` to pull the raw form submissions for your analysis.

Yes, the MCP transport layer supports both standard I/O and HTTP, letting you run the server locally or host it on Google Cloud.

Every request runs in a zero-trust, ephemeral sandbox. Vinkius handles all Kissflow API credentials securely, ensuring your process lists and form submissions are never exposed to external networks.

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