How to Use the Serviceform MCP in Google ADK

Q: How does Serviceform with Google ADK retrieve specific lead details?

Call getlead within your agent workflow. It fetches detailed, actionable information about a user who converted through the site's forms or widgets. This data is ready for deep analysis in BigQuery.

Q: Can I list all available forms using Serviceform with Google ADK?

Yes, use listforms. The tool provides a clear roster of every active form the site runs. This helps your agent understand exactly what data points are available for collection.

Q: Does Serviceform with Google ADK help list configured spaces?

Absolutely. Use the listspaces tool. This function provides a comprehensive inventory of all 'flex spaces,' which is vital for building multi-step, complex agent workflows.

Build enterprise conversion agents using Serviceform with Google ADK.

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Connect Serviceform MCP to Google ADK

Create your Vinkius account to connect Serviceform to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Serviceform with Google ADK

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Track and summarize chats

Need to audit customer conversations? Use `list_chats` by supplying criteria as a JSON string. This allows your agent to pull historical data from the chat service. The Gemini model can hold that context, letting you reason over large volumes of interaction history directly within BigQuery.

Review all potential lead sources

Before building a workflow, check out `list_spaces`. This tool exposes every configured 'flex space' on the site. It gives your agent a full overview of where data can be gathered. The agent uses this list to determine which tools are relevant for solving a user-facing business problem.

Collect comprehensive lead records

When an interaction results in a contact, the `get_lead` tool retrieves all the necessary details. This ensures your agent captures complete profiles that can be analyzed later. The structured output makes it easy for Vertex AI to ingest and analyze the data against existing customer segments in BigQuery.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Serviceform. 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 Serviceform MCP in Google ADK

Call `get_lead` within your agent workflow. It fetches detailed, actionable information about a user who converted through the site's forms or widgets. This data is ready for deep analysis in BigQuery.

Yes, use `list_forms`. The tool provides a clear roster of every active form the site runs. This helps your agent understand exactly what data points are available for collection.

You must supply specific search parameters as a JSON string via `list_chats`. The Gemini model processes this input, giving you focused chat histories relevant to your current business query.

Absolutely. Use the `list_spaces` tool. This function provides a comprehensive inventory of all 'flex spaces,' which is vital for building multi-step, complex agent workflows.

The server touches PII (Personally Identifiable Information) via `get_lead` and `list_chats`. When building agents on Google Cloud, make sure your access controls strictly govern who can view this user data.

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