How to Use the HrFlow.ai MCP in Google ADK

Q: Can I restrict which HrFlow.ai tools my Gemini agent accesses?

Yes. Google ADK lets you apply a toolnames filter. You can expose parsing tools while hiding the scoring tools.

Q: Does Google ADK support the HrFlow.ai semantic search?

Absolutely. The agent calls searchprofiles natively and uses Gemini's reasoning to interpret the semantic results.

Connect HrFlow.ai to Google ADK and let Gemini agents analyze thousands of resumes at once.

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Connect HrFlow.ai MCP to Google ADK

Create your Vinkius account to connect HrFlow.ai 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 HrFlow.ai with Google ADK

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Process massive talent pools with Google ADK

Gemini's massive context window changes how you handle applicant tracking. Feed the agent the output from `list_profiles` and watch it synthesize hundreds of candidates in seconds. You stop reading resumes and start reviewing shortlists. When you need specifics, the agent calls `parse_profile` to extract exact structured data from individual documents. You can then pipe that clean output directly into your BigQuery data warehouse for enterprise reporting. The integration handles the transit natively.

Run semantic searches across your MCP Server

Keyword searches miss qualified talent. The `search_profiles` and `search_jobs` tools use semantic filters to find the right match based on actual skills and intent. Your queries actually understand context. Your Gemini agent acts as an intelligent sourcer. It pulls active listings via `list_jobs` and cross-references them against your entire candidate database. The model finds hidden matches your human team skipped over.

Analyze career progression automatically

You want to know if a candidate is ready for a leadership role. The `unfold_profile` tool breaks down their career trajectory, identifying promotions and skill acquisitions over time. It spots the patterns you care about. If the hiring manager has specific concerns, the agent uses `ask_profile` to interrogate the candidate's history. It reads the nuance in the work experience and provides direct answers about their exact responsibilities.

Setup guide

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

Use the McpToolset class with StreamableHttpServerParameters. Pass the resulting toolset to your LlmAgent configuration.

Yes. Google ADK lets you apply a tool_names filter. You can expose parsing tools while hiding the scoring tools.

Absolutely. The agent calls `search_profiles` natively and uses Gemini's reasoning to interpret the semantic results.

Assign it via the tools array. The framework handles the transport layer automatically.

The MCP reads raw resumes and outputs structured candidate data. Google Cloud enterprise policies apply to the transit, ensuring candidate employment histories remain secure in your VPC.

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