How to Use the Manatal MCP in Google ADK

Q: How do I link Manatal to my Google ADK agent?

Initialize the McpToolset with your server URL and pass it to your agent constructor. The framework handles the connection and tool registration.

Q: Can I restrict which Manatal tools my Google ADK agent sees?

Yes. Use the toolnames filter to expose only the specific tools your agent needs. This keeps your agent's toolset clean and focused.

Bring Manatal recruitment data into your Google ADK agents and process high-volume hiring pipelines on Google Cloud.

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Connect Manatal MCP to Google ADK

Create your Vinkius account to connect Manatal 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 Manatal with Google ADK

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Deep candidate insights for Google ADK

Your agent queries candidate profiles using `get_candidate` and scans your entire pool with `list_candidates`. It translates raw candidate data into actionable hiring intelligence instantly. This integration works with your existing Google Cloud infrastructure. Your agent keeps its context window focused on the most relevant applicant details.

Syncing jobs with Google ADK agents

Access active openings through `list_jobs` and inspect specific requirements with `get_job`. Your agent uses this data to filter incoming applications for better matches. It pulls the latest data at each turn. You avoid stale information and keep your recruitment dashboard accurate across your entire team.

Structural awareness for hiring

Use `list_departments` and `list_organizations` to map candidates to your company hierarchy. Your agent understands exactly which team owns a specific job opening. This provides the necessary context for complex hiring workflows. Your agent makes decisions based on the actual layout of your business.

Setup guide

Set up Manatal 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 Manatal 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="Manatal_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Manatal tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Manatal MCP in Google ADK

Initialize the `McpToolset` with your server URL and pass it to your agent constructor. The framework handles the connection and tool registration.

The server is optimized for fast responses. Since Google ADK supports efficient transport layers, your agent experiences minimal latency when fetching candidate data.

Yes. Use the tool_names filter to expose only the specific tools your agent needs. This keeps your agent's toolset clean and focused.

All traffic stays within your configured transport. You maintain full control over the data flow between your ATS and your agent logic.

Your candidate records never touch external storage. The MCP server acts as a direct bridge, ensuring your sensitive hiring data stays within your controlled cloud environment.

Use it with your favorite AI tools

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