How to Use the BatchDialer MCP in Google ADK

Q: Can I restrict which BatchDialer tools Google ADK can access?

Yes. Use the toolnames filter in your McpToolset configuration to expose only the tools you want, like addlead. This prevents the agent from reading sensitive call logs if it doesn't need to.

Q: How does Google ADK handle high-volume BatchDialer lead imports?

The agent processes leads in batches, feeding them to addlead while checking rate limits. This keeps your BigQuery pipelines in sync with your outbound phone queues.

Q: Can I use Gemini's long context to analyze BatchDialer logs?

You certainly can. Load your logs with listcalllogs and dump the raw output directly into Gemini's context window to find patterns in call drop rates.

Run BatchDialer outreach directly from your Google ADK pipelines using this hosted MCP Server.

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Connect BatchDialer MCP to Google ADK

Create your Vinkius account to connect BatchDialer 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 BatchDialer with Google ADK

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Control Dialer Campaigns via Google ADK

The `list_campaigns` tool exposes your entire outbound phone setup to your Gemini agent. Connecting via MCP allows your script to check current dialer status before pushing new data. After identifying the target, the agent uses `get_campaign` to pull specific dialing configurations. This ensures your cloud workflows never target paused or completed campaigns.

Inject BigQuery Leads with Google ADK MCP Server

The `add_lead` tool pushes fresh prospects from your Google Cloud databases straight into your dialing lists. Your agent processes raw lead data, formats it, and inserts it into the dialer. Using `list_leads`, the agent cross-references existing records to prevent dialing the same prospect twice. This keeps your outbound campaigns clean and compliant.

Track Call Dispositions and Performance

The `list_call_logs` tool retrieves your complete outbound history directly into your Gemini context window. This lets you analyze thousands of calls using Gemini's massive 1M token capacity. Your agent matches these logs with `list_dispositions` to identify which lists yield the best contact rates. You can then feed these insights straight into Vertex AI for predictive modeling.

Setup guide

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

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Common questions about BatchDialer MCP in Google ADK

Instantiate McpToolset with our secure Vinkius StreamableHttpServerParameters URL. Pass that toolset into your LlmAgent constructor to give Gemini direct access to all ten dialer tools.

Yes. Use the tool_names filter in your McpToolset configuration to expose only the tools you want, like `add_lead`. This prevents the agent from reading sensitive call logs if it doesn't need to.

The agent processes leads in batches, feeding them to `add_lead` while checking rate limits. This keeps your BigQuery pipelines in sync with your outbound phone queues.

You certainly can. Load your logs with `list_call_logs` and dump the raw output directly into Gemini's context window to find patterns in call drop rates.

We run the MCP Server in an ephemeral, zero-trust sandbox that handles your API tokens securely. Your outbound phone numbers and lead records are processed in-memory and never stored on our servers.

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