How to Use the AirMatch Pro MCP in Google ADK

Run enterprise recruitment pipelines using Google ADK and AirMatch Pro.

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Connect AirMatch Pro MCP to Google ADK

Create your Vinkius account to connect AirMatch Pro 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 AirMatch Pro with Google ADK

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Cross-reference BigQuery with AirMatch Pro MCP Server

Connect your enterprise data warehouse to your recruiting pipeline. Your Google ADK agent pulls candidate files from BigQuery and matches them against active listings using `list_jobs` and `list_leads`. This MCP Server bridges your Google Cloud infrastructure and your external recruiting tools. The agent uses `get_lead` to pull deep profiles and feeds them directly into Gemini's massive context window.

Draft client estimates using Gemini long-context

Let Gemini analyze historical hiring costs to draft new client agreements. Your Google ADK agent reads past pricing structures via `list_estimates` and builds new deals using `create_proposal`. The agent verifies everything by calling `list_proposals` and `get_proposal`. Because Gemini handles millions of tokens, it can compare dozens of old proposals simultaneously to ensure pricing accuracy.

Audit recruiting profiles against corporate directories

Keep your internal directories and external listings perfectly in sync. Your Google ADK agent reviews your recruiter accounts via `get_profile` and matches them against active customer records using `list_customers`. The agent runs `check_airmatch_status` to ensure API availability before starting large-scale directory syncs. This prevents your Google Cloud workflows from failing midway through a run.

Setup guide

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

Yes. You can configure your Google ADK agent to query BigQuery tables and then use AirMatch Pro tools like `list_jobs` to update your external pipelines.

Configure the Vinkius MCP Server inside your Google ADK toolset setup. The agent handles the connection automatically using your single Vinkius endpoint token.

It allows the agent to ingest hundreds of pages of resume data at once before calling `create_proposal` or `list_leads` to find the perfect fit.

Yes, Google ADK supports a tool name filter when initializing your toolset, letting you hide tools like `create_proposal` if you only want read-only access.

Your customer profiles and job requirements remain isolated within your Google Cloud boundary. This MCP Server uses ephemeral execution, meaning no candidate data is ever written to disk outside your designated VPC.

Use it with your favorite AI tools

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