How to Use the Ashby MCP in Google ADK

Run enterprise-grade recruiting workflows in Google ADK using Ashby data with Gemini's million-token context.

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Connect Ashby MCP to Google ADK

Create your Vinkius account to connect Ashby 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 Ashby with Google ADK

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Parse entire pipelines with Google ADK

This MCP Server connects Gemini to your recruiting pipeline using `list_applications` to pull large batches of applicant records. The long-context window lets you analyze hundreds of applications at once. Combining this tool with BigQuery datasets allows your Google ADK agent to cross-reference past hiring trends with current open roles. You get deep analysis without hitting context limits.

Audit your job openings instantly

The server retrieves active roles using `list_jobs` to match them against your company's headcount plans. Your agent checks open requisitions against external data sources to find discrepancies. When you need specific requirements, `get_job_info` fetches the complete description and hiring team details. This keeps your Google Cloud agents fully informed during automated MCP reporting runs.

Trace candidate journeys in real time

Your agent tracks candidate progress by calling `get_candidate_info` during scheduled batch runs. It maps out where bottlenecks occur in your hiring pipeline. Running `list_interviews` alongside candidate lookups gives you a clear picture of team capacity. You can pipe this data directly into Vertex AI to predict time-to-hire metrics.

Setup guide

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

Install the ADK and define the HTTP transport using your Vinkius endpoint. Pass the toolset to your LlmAgent constructor to instantly expose the MCP tools to Gemini.

Yes, the Google ADK supports tool filtering if you want to limit exposure, but Gemini's large context easily manages all ten tools. You can expose everything from `get_account_check` to `search_jobs` without performance drops.

Load your enterprise data from BigQuery into your agent's context, then use `search_candidates` to find matching records in your applicant tracking system. The agent acts as the bridge between your data warehouse and your hiring pipeline.

This MCP setup supports both standard Stdio and HTTP transports. For cloud deployments on Google Cloud Run, the HTTP option is the most reliable way to connect.

Your applicant records, salaries, and resume details are processed in an isolated, zero-trust sandbox. Vinkius manages the authentication tokens, preventing raw Ashby credentials from being exposed to your Google Cloud environment.

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