How to Use the Sally MCP in Google ADK

Q: How do I link Sally with my Google ADK agent?

Initialize the McpToolset with your server URL and add it to your LlmAgent configuration. You can use a tool name filter to expose only the specific functions your agent requires.

Q: Does Sally work with Gemini long-context in Google ADK?

Yes. You can feed large project histories retrieved via listprojects into your context window. It allows your agent to reason over massive amounts of operational data.

Q: Can I restrict tools for Sally in Google ADK?

You can. Use the toolnames filter to limit the agent's access to only what is necessary for its specific role, such as just reading tasks.

Bridge your Google ADK agents to Sally. Sync frontline project data with your Google Cloud infrastructure and Gemini-powered workflows.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Sally MCP to Google ADK

Create your Vinkius account to connect Sally to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Sally with Google ADK

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Frontline task control for Google ADK

Your agent manages heavy workloads by calling `create_task` and `update_task` directly from your Gemini-powered pipelines. It automates the routine work that keeps deskless teams moving. This MCP Server acts as the bridge between your enterprise data and field operations. Your agent keeps project statuses updated without manual intervention.

Connect Sally MCP Server to BigQuery workflows

Feed timesheet data into your analytics pipeline using `get_timesheet_report`. Your agent retrieves this data and pushes it straight to your cloud storage for deeper analysis. Use `list_tasks` to gather the raw input your agent needs. It provides the visibility required to make data-driven decisions on the fly.

Mobile-ready team updates with Google ADK

Agents use `add_comment` to broadcast instructions to the team. This keeps your field staff connected to the same source of truth as your backend systems. `get_board` gives your agent the layout of current work. It helps the system identify bottlenecks before they impact your delivery timelines.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Sally. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Sally MCP in Google ADK

Initialize the `McpToolset` with your server URL and add it to your `LlmAgent` configuration. You can use a tool name filter to expose only the specific functions your agent requires.

Yes. You can feed large project histories retrieved via `list_projects` into your context window. It allows your agent to reason over massive amounts of operational data.

Vinkius manages your endpoint tokens securely. You never expose raw keys in your code, keeping your Google Cloud environment protected.

You can. Use the tool_names filter to limit the agent's access to only what is necessary for its specific role, such as just reading tasks.

Your timesheet data is restricted to the authenticated user session. The server acts as a gatekeeper, ensuring only authorized agent requests can retrieve sensitive labor reports.

Use it with your favorite AI tools

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