How to Use the AntEater MCP in Google ADK

Q: Can I restrict which AntEater tools my Google ADK agent can access?

Yes, you can. Use the toolnames filter when initializing your toolset to expose only safe tools like searchcontacts while blocking administrative tools like getuseractivity.

Give your Google ADK enterprise agents direct access to team communication logs and shared contacts in Gemini.

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Connect AntEater MCP to Google ADK

Create your Vinkius account to connect AntEater 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 AntEater with Google ADK

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Feed contact history to Google ADK agents

This MCP Server feeds contact history and communication logs directly to your Google ADK agents. Enterprise agents need deep context to make smart decisions. By calling `get_contact_history` and `search_contacts`, your Gemini models can digest years of client interactions. This fits perfectly with Gemini's massive million-token context window. The agent pulls raw communication history and analyzes the entire relationship arc in a single turn.

Audit team updates across Slack and email

The activity search tools in this server track team updates across Slack and email. No more manual status reports. Your agent uses this MCP tool to run `search_activity` and `list_recent_activity` to pull real-time updates. You can feed this raw text directly into Vertex AI pipelines. The agent cross-references Slack chatter with your BigQuery datasets to spot bottlenecks before they stall your project.

Query live team directories on demand

This directory lookup server queries live team structures and user roles on demand. Keep your agent informed about who is who. Using `list_users` and `get_user_activity`, your agent identifies active team members and checks what they are working on. This eliminates stale directory issues. When a client emails, the agent checks `get_profile` to confirm the account owner before drafting a response.

Setup guide

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

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Common questions about AntEater MCP in Google ADK

Install the ADK via pip install google-adk and import McpToolset. Pass the Vinkius HTTP endpoint into StreamableHttpServerParameters and add the toolset to your LlmAgent configuration. This registers the MCP tools natively.

Yes, you can. Use the `tool_names` filter when initializing your toolset to expose only safe tools like `search_contacts` while blocking administrative tools like `get_user_activity`.

The MCP Server passes structured contact and activity data directly to the Google ADK. Gemini's large context window allows the model to process massive outputs from `get_contact_history` without running out of memory.

It supports both. For managed cloud deployments on Google Cloud, we recommend using the HTTP transport to keep your agent stateless and easy to scale.

Your data remains strictly inside your Google Cloud perimeter. The Vinkius gateway acts as a zero-trust bridge, processing requests in ephemeral memory with token-based authentication that you control.

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