How to Use the Namely MCP in Google ADK

Q: Can my Google ADK agent see our custom fields in Namely?

Yes. The listfields tool lets your agent inspect the names and types of any custom fields you've configured in Namely. This allows it to construct accurate queries for employee data.

Connect your Gemini agent to your Namely org chart and run HR analytics right inside Google Cloud.

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Connect Namely MCP to Google ADK

Create your Vinkius account to connect Namely 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 Namely with Google ADK

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Query Your Org Chart in Real Time

This MCP server gives your Google ADK agent the ability to look up employee and team information directly from Namely. It can use `get_profile` to find a specific person's role or use `list_profiles` to fetch an entire department's roster. Because Gemini models support long contexts, your agent can load the results of `list_teams` and `list_groups` to hold a complete picture of the organization. This lets it answer complex questions about reporting lines and team structures without repeated API calls.

Enrich Your BigQuery Data with HR Context

This is where it gets powerful. Your agent can pull live HR data from this Namely MCP server and use it to add context to your existing datasets in Google Cloud. Use the `list_jobs` tool to get current job titles and match them against project management data. You can also pull reports directly with `list_reports`. Imagine an agent that joins your latest headcount report from Namely with financial projections from a BigQuery table, giving you a live view of personnel costs.

Build Enterprise Agents with this Google ADK MCP Server

This MCP server exposes core company information for your enterprise agents. The `list_announcements` tool provides a feed of internal news, which your agent can summarize or route to the right people. Similarly, `list_events` gives your agent a timeline of birthdays and anniversaries. It's the kind of data that helps an agent perform tasks that require awareness of the company's social fabric, all within your secure Google Cloud environment.

Setup guide

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

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Common questions about Namely MCP in Google ADK

You get a Vinkius URL after subscribing. In your Python code, you'll use it to create an `McpToolset` with `StreamableHttpServerParameters` and pass it to your `LlmAgent`.

A great starting point is a resource planning agent. It can use `list_profiles` and `list_teams` from Namely to identify available engineers and cross-reference their skills against project requirements stored in a Google Sheet or BigQuery.

Not at all. The ADK is built to consume toolsets like this one. You point it at the server URL, and it handles the tool discovery. You can even use `tool_names` to filter which Namely tools the agent is allowed to see.

Yes. The `list_fields` tool lets your agent inspect the names and types of any custom fields you've configured in Namely. This allows it to construct accurate queries for employee data.

Vinkius provides a secure, single-tenant connection to the Namely API that handles employee profile and team data. All communication between your agent on Google Cloud and Vinkius is encrypted, ensuring your HR data doesn't leak.

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