How to Use the Crelate Talent CRM MCP in Google ADK

Q: Can Google ADK search for specific candidates in Crelate Talent CRM?

It uses the searchcontactsbyname tool to find exact matches. The agent passes the keyword, and the server returns the matching profile IDs and basic details.

Q: Does Crelate Talent CRM let Google ADK read internal recruiter notes?

The getcontactnotes tool fetches all internal feedback attached to a candidate. Gemini can then summarize those notes and compare them against Vertex AI models you have trained.

Feed Crelate Talent CRM candidate data straight into Google ADK to build enterprise recruiting agents on Gemini via MCP.

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Connect Crelate Talent CRM MCP to Google ADK

Create your Vinkius account to connect Crelate Talent CRM 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 Crelate Talent CRM with Google ADK

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Process Massive Candidate Pools

Gemini models hold over a million tokens in context. You can dump hundreds of candidate profiles into a single prompt. Your agent pulls this list using `list_contacts` and evaluates them simultaneously. BigQuery integration makes this even stronger. An agent compares historical hiring data from your data warehouse against live profiles from Crelate. It pinpoints exactly who fits the role.

Gemini Agents Powered by MCP Server

Enterprise recruiting means managing multiple client companies. Your agent maps out your entire client base by calling `list_companies`. It then drills into specific requisitions with `get_job_details`. You filter which tools the agent sees using the tool_names parameter. If a specific agent only needs to analyze jobs, you restrict it from seeing candidate data entirely.

Monitor Recruiter Output

Connecting your ATS to Google Cloud infrastructure opens up deep reporting. The agent pulls daily call logs and email histories via `list_recent_activities`. It checks team capacity by running `list_crelate_users`. Setup requires the google-adk package. You initialize a McpToolset with your Vinkius HTTP URL and attach it to your LlmAgent. The MCP connection runs securely over HTTP transport.

Setup guide

Set up Crelate Talent CRM 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 Crelate Talent CRM 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="Crelate Talent CRM_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Crelate Talent CRM tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Crelate Talent CRM MCP in Google ADK

Import McpToolset from the SDK and configure it with StreamableHttpServerParameters. Pass that toolset directly to your LlmAgent. The Gemini model will immediately recognize the available MCP tools.

It uses the search_contacts_by_name tool to find exact matches. The agent passes the keyword, and the server returns the matching profile IDs and basic details.

The get_contact_notes tool fetches all internal feedback attached to a candidate. Gemini can then summarize those notes and compare them against Vertex AI models you have trained.

Yes. You apply a filter to the McpToolset configuration. Just expose list_companies and hide the other nine tools to keep the agent focused.

Salary history and internal recruiter feedback travel through a zero-trust encrypted tunnel. Authentication happens via a single endpoint token, and Vinkius discards the memory state immediately after the request finishes.

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