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How to Use the Chiirp MCP in Google ADK

Feed your BigQuery marketing data directly into Chiirp campaigns using Google ADK and Gemini long-context agents.

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Google ADK

Connect Chiirp MCP to Google ADK

Create your Vinkius account to connect Chiirp 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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Bulk contact matching using this MCP Server

The `search_contacts` tool queries your Chiirp database by phone number to prevent duplicate records. When paired with Google ADK, your Gemini agent can process thousands of leads from a BigQuery export in a single run, utilizing Gemini's long-context window to cross-reference data. After finding matching records, the agent uses `update_contact` to refresh outdated fields. This keeps your Google Cloud CRM data and your SMS marketing platform perfectly mirrored without manual CSV uploads.

Sequence mapping via Google ADK

The `list_sequences` tool retrieves all active automation flows from your account. Google ADK lets your agent pull this list and compare it against your Vertex AI customer journey models to determine the best sequence for each lead. Once the model selects the path, the agent uses `apply_tag` to kick off the chosen sequence. This turns your static Google Cloud analytics into direct, automated SMS and email actions.

Restricting Google ADK tool access

The `get_profile` tool retrieves sensitive Chiirp account metadata that you might want to hide from general-purpose agents. Google ADK allows you to apply a `tool_names` filter to your toolset to restrict the exposed MCP Server capabilities. By excluding administrative actions and only exposing `create_contact` or `list_tags`, you ensure your customer-facing agents can only write new leads and never read your entire system configuration.

Setup guide

Set up Chiirp 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. 1

    Install Google ADK

    Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.

  2. 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. 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. 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 Chiirp 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="Chiirp_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chiirp tools via MCP.",
    tools=mcp_tools,
)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Chiirp. 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 Chiirp MCP in Google ADK

You initialize `McpToolset` with the HTTP transport URL provided by Vinkius. Pass this toolset directly to your `LlmAgent` to instantly grant Gemini access to tools like `list_contacts` and `apply_tag`.
Yes, the agent can call `list_campaigns` to pull active marketing setups. It can then feed this data into Vertex AI to analyze campaign performance against your enterprise benchmarks.
Gemini's 1M+ token window allows the agent to ingest the entire output of `list_contacts` and `list_tags` simultaneously. This lets the agent make highly contextual decisions about which tags to apply without hitting context limits.
Google ADK supports concurrent execution of tools. Your agent can search for multiple contacts using `search_contacts` and update them with `update_contact` in parallel batches to speed up processing.
All contact profiles and phone numbers fetched via `get_contact` remain within your Google Cloud boundary and the ephemeral Vinkius sandbox. No customer data is written to disk or used for model training.

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