How to Use the ApplicantStack MCP in Google ADK

Q: Can I restrict which ApplicantStack tools Google ADK can access?

Yes, you can use the toolnames filter in Google ADK to restrict exposure. For example, you can expose only listjobs and getjob if you want a read-only agent.

Q: How does Gemini use ApplicantStack data within Google ADK?

Gemini ingests structured JSON from tools like listcandidates directly into its context. The Google ADK agent can then reason over candidate profiles and job requirements to make matching recommendations.

Connect Gemini's long-context models to ApplicantStack using Google ADK.

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Connect ApplicantStack MCP to Google ADK

Create your Vinkius account to connect ApplicantStack 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 ApplicantStack with Google ADK

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Process hiring pipelines with Google ADK

The `list_candidates` tool lets Google ADK agents pull entire batches of applicant profiles into Gemini's massive context window using our MCP Server. You analyze hundreds of resumes at once alongside your internal hiring guidelines. Your Google ADK agent uses `get_candidate` to drill down into specific ApplicantStack resumes when the model flags an exceptional match. This direct access lets you build high-volume screening pipelines directly on Google Cloud.

Map recruiting data to cloud databases

The `list_jobs` tool fetches active job listings so your Google ADK agent can map them to external market trends. You cross-reference these open roles with your BigQuery talent data to identify regional hiring gaps. To ensure your database sync is healthy, the `get_account_check` tool verifies your ApplicantStack connection parameters in real time. This keeps your Google Cloud pipeline synchronized with your actual ATS listings.

Manage candidate stages from Gemini agents

The `update_candidate` tool updates applicant stages in ApplicantStack as your Google ADK agent completes screening tasks. You define the logic, and the agent executes the status change. Once a hire is finalized, the `list_hires` tool pulls onboarding records so your Google ADK workflow can trigger cloud-based background checks. This connects your recruiting pipeline to your enterprise HR infrastructure.

Setup guide

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

Use the McpToolset class with your Vinkius HTTP endpoint URL. Pass this toolset into your Google ADK LlmAgent constructor to expose the hiring tools to Gemini.

Yes, you can use the tool_names filter in Google ADK to restrict exposure. For example, you can expose only list_jobs and get_job if you want a read-only agent.

Gemini ingests structured JSON from tools like list_candidates directly into its context. The Google ADK agent can then reason over candidate profiles and job requirements to make matching recommendations.

Yes, this setup is designed for cloud deployment. You configure the Google ADK agent in Python, point it to the Vinkius MCP Server, and run it as a serverless container.

All candidate data, including names, emails, and resume text, is transmitted over encrypted HTTPS channels. The Vinkius MCP sandbox executes tool calls ephemerally, ensuring no hiring data is cached or stored outside your Google Cloud environment.

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