How to Use the Listen Notes MCP in Google ADK

Q: Can I restrict the Google ADK agent to only search Listen Notes without fetching details?

Yes, you can pass an optional toolnames filter to the toolset. This restricts the agent's access to searchpodcastsorepisodes while blocking tools like getpodcastdetails or getepisodedetails.

Q: How does the agent handle curated lists?

The agent invokes getcuratedpodcasts to retrieve hand-picked lists compiled by listeners. It then parses these lists to extract show IDs and fetch individual episode details.

Connect Gemini models to the Listen Notes directory using Google ADK to analyze podcast metadata alongside BigQuery datasets.

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Connect Listen Notes MCP to Google ADK

Create your Vinkius account to connect Listen Notes 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 Listen Notes with Google ADK

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Inject podcast metadata into Gemini long-context windows

`get_podcast_details` retrieves the entire episode history and metadata of a show through the MCP Server, feeding thousands of tokens of structured text directly into Google ADK. Gemini models process these massive payloads to analyze long-term content trends or summarize multi-year show directories. Because Google ADK handles long-context reasoning natively, your agent can compare detailed show notes against enterprise data in BigQuery. The model identifies patterns across hundreds of episodes without running out of context space.

Search podcast databases using Google ADK tools

`search_podcasts_or_episodes` executes queries against the global podcast database using specific search parameters. The Google ADK agent parses these results and writes the structured output directly to your cloud storage or database. After running the query, the agent filters the JSON response and prepares the data for downstream machine learning pipelines in Vertex AI.

Discover regional trends using this Google ADK MCP Server

`get_best_podcasts` pulls top-ranking shows based on genre filters that you or your agent specify. The agent uses this data to map out regional content popularity and feed the results into your analytical dashboards. By combining this with `list_podcast_genres`, the Google ADK toolset builds a structured map of the podcast ecosystem. Your agent queries the genres, selects the target ID, and pulls the best podcasts to analyze audience demographics.

Setup guide

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

You initialize the server using the McpToolset class with the HTTP transport parameters pointing to your Vinkius endpoint. Google ADK auto-discovers all seven tools, making them instantly available to your Gemini-powered LlmAgent.

Yes, you can pass an optional tool_names filter to the toolset. This restricts the agent's access to `search_podcasts_or_episodes` while blocking tools like `get_podcast_details` or `get_episode_details`.

Google ADK does not automatically cache tool outputs, meaning every agent action triggers a real-time request to the MCP Server. If you want to avoid repeated API calls for static metadata, you should implement caching at your application level or within your Google Cloud database.

The agent invokes `get_curated_podcasts` to retrieve hand-picked lists compiled by listeners. It then parses these lists to extract show IDs and fetch individual episode details.

Your search inputs and episode payloads are processed in a secure, zero-trust V8 isolate. Vinkius executes the requests ephemerally, ensuring that no search terms or audio metadata are logged or exposed to third parties during transit.

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