How to Use the Mailshake MCP in Google ADK

Q: How do I load the Mailshake MCP Server into Google ADK?

Install the SDK and initialize McpToolset with StreamableHttpServerParameters. Pass that toolset into your LlmAgent under the tools argument.

Q: Can I restrict my Google ADK agent to read-only tools on the MCP Server?

Yes. Use the toolnames filter when configuring the toolset. You can expose getcampaigndetails while hiding the pausing functions.

Q: Does Google ADK support bulk Mailshake prospect uploads via this MCP integration?

The agent uses addprospectstocampaign, which accepts JSON payloads for multiple recipients. Rate limits apply based on your API tier, so structure your agent loops accordingly.

Q: How do Gemini models interact with Mailshake lead history?

They read the output of getleadhistory directly into context. Because Gemini handles massive token counts, you can feed it hundreds of lead histories at once for pattern recognition.

Give your Google ADK enterprise agents direct control over the Mailshake MCP Server.

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Connect Mailshake MCP to Google ADK

Create your Vinkius account to connect Mailshake 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 Mailshake with Google ADK

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Manage Mailshake Campaigns with Google ADK

The `list_outreach_campaigns` tool feeds active sequence data directly into your Gemini context window. Your agent reads the current state of your outreach architecture without leaving the Google Cloud environment. If a sequence needs to stop, the agent executes `pause_outreach_campaign`. You can filter which tools the agent sees using the `tool_names` parameter in your setup, keeping destructive actions away from read-only agents.

Push BigQuery Leads into Sequences

The `add_prospects_to_campaign` tool takes JSON payloads to insert new contacts into your pipelines. Your enterprise agents can pull rows from BigQuery, format the data, and push it straight to the API. To verify ingestion, the agent calls `list_campaign_recipients`. Gemini's massive 1M+ token context window means you can dump thousands of recipient records into memory for cross-referencing against Vertex AI datasets.

Analyze Lead History and Messaging

The `list_campaign_leads` and `get_lead_history` tools extract engagement timelines for qualified contacts. Your agent uses this raw timeline data to score prospect intent. When deeper context is required, `list_outreach_messages` and `get_message_content` pull the exact email threads. The agent processes these threads alongside your internal CRM records to determine the next best action.

Setup guide

Set up Mailshake 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 Mailshake 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="Mailshake_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mailshake 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 Mailshake. 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 Mailshake MCP in Google ADK

Install the SDK and initialize `McpToolset` with `StreamableHttpServerParameters`. Pass that toolset into your `LlmAgent` under the `tools` argument.

Yes. Use the `tool_names` filter when configuring the toolset. You can expose `get_campaign_details` while hiding the pausing functions.

The agent uses `add_prospects_to_campaign`, which accepts JSON payloads for multiple recipients. Rate limits apply based on your API tier, so structure your agent loops accordingly.

They read the output of `get_lead_history` directly into context. Because Gemini handles massive token counts, you can feed it hundreds of lead histories at once for pattern recognition.

The integration reads prospect email addresses, message body text, and sequence timelines. Vinkius handles the authorization via a zero-trust architecture, meaning your Google Cloud environment only needs one ephemeral token to connect.

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