How to Use the Xeno-canto MCP in Google ADK

Query global bird sound libraries and embed results directly in your Google ADK workflows.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Xeno-canto MCP to Google ADK

Create your Vinkius account to connect Xeno-canto 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 Xeno-canto with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Contextual Search Retrieval

The `search_recordings` tool lets you pull data from Xeno-canto’s massive collection. You provide parameters—say, the genus (`g`) and a country code (`cnt`)—and your agent returns structured recordings. This is perfect for building enterprise agents that need specific, external knowledge integrated into their reasoning pipeline.

BigQuery Integration

Because the Google ADK supports native BigQuery integration, you can write a workflow that searches using `search_recordings` and then immediately load those results for analysis. No need to export and re-import data. It keeps your entire process contained within the secure scope of Google Cloud infrastructure.

Long Context Processing

The Gemini models powering the ADK can hold huge context windows (1M+ tokens). This means you can pass a large list of recordings returned by `search_recordings` and have your agent reason over them all at once. Instead of processing results chunk-by-chunk, the whole dataset stays in context for complex analysis.

Setup guide

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

You pass the desired parameters (like location or species) to `search_recordings` within your LlmAgent. The framework then manages fetching and integrating that data into your running workflow.

Yes, the tool supports detailed filtering using parameters for genus (`g`), country (`cnt`), or specific species. You can combine these filters to narrow down your search results.

The agent handles bird sound recording metadata. This includes detailed location and species information gathered by the `search_recordings` tool.

You can. Since the underlying models support massive context windows, you're not limited by typical message limits when working with `search_recordings` data.

This server processes bird sound recording metadata. Since it runs within your dedicated Google Cloud environment, you maintain full control over how this information is used and stored.

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