How to Use the Autobound MCP in Google ADK

Q: Does Autobound support parallel tool execution in Google ADK?

It does. Gemini can trigger enrichbulk to process dozens of prospects simultaneously, speeding up your data enrichment pipelines inside Google Cloud.

Q: How do I monitor active outbound sequences?

Use listcampaigns to fetch your current sales sequences. Your agent can query this list via the MCP server to decide which campaign fits a prospect's profile before enrolling them.

Scale personalized B2B outbound sequences using Google ADK and Gemini's long-context reasoning.

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Connect Autobound MCP to Google ADK

Create your Vinkius account to connect Autobound 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 Autobound with Google ADK

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Perplexity

Analyze complex buyer intent inside Google ADK

`search_signals` pinpoints high-value accounts showing active buying behavior. Gemini's massive context window lets you feed thousands of raw data points from BigQuery directly to your agent to find these leads. Running `get_signal` extracts the context once a signal is flagged. This allows your Google Cloud pipeline to respond to market shifts in real time.

Enrich enterprise leads with this MCP Server

`enrich_company` and `enrich_contact` scrape public data to find the exact decision-makers you need. Pulling complete target profiles is simple with this setup. Mapping the retrieved data straight to your BigQuery tables keeps your CRM clean. You get structured contact records without manual data entry or complex custom scraping scripts.

Generate personalized copy at scale

`generate_email` drafts highly specific cold outreach based on the prospect's recent company news and role. Standard templates fail to get replies, but personalized copy converts. Calling `generate_linkedin` creates short, punchy messages that match the tone of your email campaigns. This ensures a multi-channel approach that works.

Setup guide

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

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

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Common questions about Autobound MCP in Google ADK

Instantiate the toolset using the StreamableHttpServerParameters class with your Vinkius endpoint. Pass this MCP toolset to your LlmAgent to make the sales tools available to Gemini.

Yes. Feed your BigQuery rows into Gemini's long context, then let the agent call `generate_email` to write custom messages for every row in your database.

It does. Gemini can trigger `enrich_bulk` to process dozens of prospects simultaneously, speeding up your data enrichment pipelines inside Google Cloud.

Use `list_campaigns` to fetch your current sales sequences. Your agent can query this list via the MCP server to decide which campaign fits a prospect's profile before enrolling them.

All company profiles and buyer signals processed by the tools run in an isolated sandbox. Vinkius uses zero-trust architecture, ensuring your proprietary sales data never trains public models.

Use it with your favorite AI tools

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