How to Use the Gainsight CS MCP in Google ADK

Q: How can I use Google ADK and Gainsight CS to prioritize my team's work?

An agent can use listcockpittasks to fetch all open tasks and gettaskmetadata for details like due dates. By combining this with customer data from getcompanyhealth, the agent can build a prioritized worklist for your CSMs.

Q: Can I create a 'daily briefing' agent for Gainsight CS with Google ADK?

Absolutely. Set up a scheduled agent that calls listcallstoaction and listcockpittasks assigned to a specific user. The agent can summarize the day's priorities and send it via Google Chat or email.

Q: What's the best way to get started with Google ADK and Gainsight CS?

Start simple. Create an agent with one tool, like listcustomercompanies, and just have it print the list. Once that's working, add getcompanyhealth to get more detail. This iterative approach is the fastest way to build a useful agent.

Q: Can I restrict which Gainsight tools my Google ADK agent can use?

Yes. The McpToolset constructor in the Google ADK takes a toolnames argument. You can pass a list of strings, like 'getcompanyhealth', 'listtimelineevents', to expose only those specific tools to the agent.

Connect Gainsight CS to your Google Cloud data. Build Gemini-powered agents with Google ADK to act on customer health and timeline events.

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Connect Gainsight CS MCP to Google ADK

Create your Vinkius account to connect Gainsight CS 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 Gainsight CS with Google ADK

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Unify CS and BigQuery Data

Your agent can now bridge the gap between your product data and your customer success platform. Use Google ADK to have an agent pull a customer list with `list_customer_companies`, cross-reference it with usage metrics in BigQuery, and then decide which accounts need attention. This isn't just about reading data. The agent can then take action, like using `log_timeline_activity` to post a 'Low Usage' note directly to that customer's timeline in Gainsight. It's a closed-loop system that lives where your data lives.

Long-Context Customer Review with Google ADK

Gemini's long-context window changes how agents can work. Your agent can call `list_timeline_events` for a high-value customer and get their entire interaction history in a single prompt. No more paginating or losing context. With the full history loaded, the agent can reason about the customer relationship from start to finish. It can spot trends, identify recurring issues, and check `get_company_health` to see how past events influenced the current score, all before recommending a course of action.

Build Enterprise Agents on GCP

The Gainsight CS MCP server fits right into your existing Google Cloud workflow. Just instantiate the `McpToolset` with your server URL and pass it to your `LlmAgent`. You can even filter which tools are exposed to which agent. For example, you could give a junior agent access to only read-only tools like `list_crm_people` and `get_person_details`. A senior agent, on the other hand, gets access to `log_timeline_activity`. This MCP setup makes granular control simple.

Setup guide

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

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Common questions about Gainsight CS MCP in Google ADK

An agent can use `list_cockpit_tasks` to fetch all open tasks and `get_task_metadata` for details like due dates. By combining this with customer data from `get_company_health`, the agent can build a prioritized worklist for your CSMs.

Absolutely. Set up a scheduled agent that calls `list_calls_to_action` and `list_cockpit_tasks` assigned to a specific user. The agent can summarize the day's priorities and send it via Google Chat or email.

Start simple. Create an agent with one tool, like `list_customer_companies`, and just have it print the list. Once that's working, add `get_company_health` to get more detail. This iterative approach is the fastest way to build a useful agent.

Yes. The `McpToolset` constructor in the Google ADK takes a `tool_names` argument. You can pass a list of strings, like `['get_company_health', 'list_timeline_events']`, to expose only those specific tools to the agent.

The server processes specific Gainsight CS data points: company records, CTAs, and task metadata. Your connection is secured through Vinkius's single-token endpoint, and all operations run in isolated, temporary environments that are destroyed after use.

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