How to Use the Bird (MessageBird) MCP in Google ADK

Q: How do I register the Bird (MessageBird) MCP Server tools inside Google ADK?

Install the package with pip install google-adk and configure McpToolset with your HTTP server parameters. Pass this toolset into the tools parameter of your LlmAgent. The Gemini model will automatically detect the Bird tools and call them when needed.

Feed Bird (MessageBird) contact data directly into Gemini models using the Google ADK and this managed MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Bird (MessageBird) MCP to Google ADK

Create your Vinkius account to connect Bird (MessageBird) 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.

GDPR Free for Subscribers

Setup Bird (MessageBird) with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Inject Bird logs into Gemini long-context

`list_messages` and `list_conversations` pull complete message threads directly into the Google ADK context. Because Gemini models handle over 1 million tokens, your agent can analyze years of customer chat history from Bird without running out of memory. The agent reads the entire history to detect sentiment, extract recurring issues, or draft context-aware replies. You don't need to build complex chunking pipelines because the Google ADK passes the raw message payloads straight to the model.

Sync CRM data with BigQuery via Google ADK

`list_contacts` and `get_contact` fetch customer profile data that your agent can match against enterprise tables in BigQuery. The Google ADK lets you write agents that cross-reference active Bird contacts with offline warehouse data in real-time. If a contact is missing or outdated, the agent calls `create_contact` or `update_contact` with JSON identifiers. This keeps your communication hub and your Google Cloud data lake perfectly aligned without manual ETL scripts.

Run automated voice log analysis in Google ADK

`list_calls` and `get_call` expose voice metadata to your Gemini agent for automated quality assurance. Your agent flags calls with unusual durations or frequent occurrences directly inside your Google Cloud console. This MCP Server exposes these tools using the `McpToolset` class. You pass the toolset into your `LlmAgent` to give Gemini immediate access to your Bird voice logs.

Setup guide

Set up Bird (MessageBird) 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 Bird (MessageBird) 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="Bird (MessageBird)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Bird (MessageBird) 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 Bird. 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.

Connect Bird (MessageBird) now

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 Bird (MessageBird) MCP in Google ADK

Install the package with `pip install google-adk` and configure `McpToolset` with your HTTP server parameters. Pass this toolset into the `tools` parameter of your `LlmAgent`. The Gemini model will automatically detect the Bird tools and call them when needed.

Yes, you can filter the tools by passing a specific list of names to the toolset configuration. For example, you can limit the agent to only `list_messages` and `send_message` if you want to block contact modification tools. This keeps your agent's scope narrow and secure.

Yes, the Google ADK supports both transport methods. Since Vinkius hosts the server, you will configure it using the HTTP transport with your unique endpoint token. This keeps the connection secure and managed.

Gemini uses native function calling to evaluate the descriptions of tools like `get_conversation` or `send_message`. When a user query requires communication data, the model outputs a tool call. The Google ADK executes this call and returns the result to the model.

Your Bird credentials and message payloads are never exposed to the LLM or stored in the Google ADK environment. Vinkius manages the authentication layer securely in an ephemeral V8 sandbox. This ensures your communication tokens remain completely hidden from the agent's context.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript