How to Use the Fountain MCP in Google ADK

Q: How do I load Fountain MCP Server tools into Google ADK?

Install google-adk. Create a McpToolset using StreamableHttpServerParameters with your endpoint URL. Pass that toolset to your LlmAgent.

Q: Can Google ADK filter which Fountain tools the agent sees?

Yes. You pass an optional toolnames list when initializing the toolset. The agent will only auto-discover the tools you explicitly allow.

Feed Fountain MCP Server data directly into Google ADK agents for massive-scale Gemini reasoning.

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Connect Fountain MCP to Google ADK

Create your Vinkius account to connect Fountain 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 Fountain with Google ADK

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Match Openings to BigQuery

The `list_job_posts` and `list_openings` tools fetch your active requisitions alongside `get_opening_details` for deep metadata. Your Gemini agent reads every requirement, location constraint, and pay band. It knows exactly what you need. Matching this data against internal records is where Google ADK shines. Your agent pulls the opening details and cross-references them with capacity models in BigQuery. You get instant visibility into whether your hiring targets match your operational reality.

Google ADK Hiring Goals

Tracking recruitment velocity depends on the `list_hiring_goals` and `list_workers` tools. The agent checks your target headcount against the actual number of hired employees. It spots shortfalls before they become operational crises. Throwing this data into a massive context window changes how you analyze trends. The agent looks at six months of hiring goals and worker data simultaneously. The Fountain MCP Server feeds this raw data straight into your Vertex AI pipeline.

Map Applicant Funnels

Mapping candidate drop-off requires the `list_funnels` and `list_applicants` operations. Your system pulls the entire pipeline structure and counts the candidates stuck in each phase. It highlights bottlenecks instantly. You restrict which operations the agent sees using the `tool_names` filter. If you only want the agent analyzing funnels, you hide the applicant data. This keeps the agent focused and reduces token waste.

Setup guide

Set up Fountain 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 Fountain 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="Fountain_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Fountain 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 Fountain. 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 Fountain MCP in Google ADK

Install `google-adk`. Create a `McpToolset` using `StreamableHttpServerParameters` with your endpoint URL. Pass that toolset to your `LlmAgent`.

Yes. You pass an optional `tool_names` list when initializing the toolset. The agent will only auto-discover the tools you explicitly allow.

Yes. You can write an agent that fetches candidate data from Fountain and runs SQL queries against your internal BigQuery datasets in the same turn.

Gemini processes millions of tokens at once. You can dump thousands of applicant records from the MCP server directly into the prompt without hitting limits.

Processing hiring goals and worker details requires strict security. Vinkius handles authentication at the gateway so users only need one endpoint token. The ephemeral containers spin down immediately after the agent finishes its task.

Use it with your favorite AI tools

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