How to Use the Buzzsprout MCP in Google ADK

Q: How do I register the Buzzsprout toolset in Google ADK?

Instantiate McpToolset with your Vinkius HTTP URL. Pass that toolset to your LlmAgent to instantly expose all Buzzsprout podcast tools to Gemini.

Q: Can my Google ADK agent cross-reference Buzzsprout with BigQuery?

Yes. Your agent can read episode stats using listepisodes and query your BigQuery datasets in the same run to generate performance reports.

Q: Does this MCP Server support restricted tool access?

Yes. You can use the toolnames filter in Google ADK to restrict your agent to read-only tools like getepisode and block destructive tools.

Feed Buzzsprout data directly to your Google ADK agents using our managed MCP Server to run smart podcast workflows.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Buzzsprout MCP to Google ADK

Create your Vinkius account to connect Buzzsprout 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 Buzzsprout with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Enterprise Podcast Analytics with Google ADK

The `get_podcast_info` and `get_account_info` tools pull your core Buzzsprout metrics directly into your Gemini agent. This allows your Google ADK agent to parse your entire podcast catalog alongside your cloud data. Since Gemini supports long-context reasoning, you can feed years of performance data retrieved by `list_episodes` into a single prompt. Your agent spots trends that standard dashboards miss.

Automated Feed Updates via MCP Server

The `update_episode` tool allows your Google ADK agent to modify episode titles, descriptions, and show notes. You can write scripts that pull fresh performance data from BigQuery and update your Buzzsprout feed. This removes manual copy-pasting between your data warehouse and your podcast host. The agent executes the updates directly using the schema exposed by the MCP Server.

BigQuery to Podcast Publishing

The `create_episode` tool lets your agent publish new audio files directly from your Google Cloud Storage buckets. Your Google ADK agent coordinates the upload, drafts the description, and sets the schedule. This setup replaces fragile custom API scripts with a single declarative agent. Your agent checks your storage bucket, formats the metadata, and runs the creation tool.

Setup guide

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

Instantiate `McpToolset` with your Vinkius HTTP URL. Pass that toolset to your `LlmAgent` to instantly expose all Buzzsprout podcast tools to Gemini.

Yes. Your agent can read episode stats using `list_episodes` and query your BigQuery datasets in the same run to generate performance reports.

Because Google ADK uses Gemini's 1M+ token context, you can load your complete Buzzsprout history via `list_episodes` without running out of memory.

Yes. You can use the `tool_names` filter in Google ADK to restrict your agent to read-only tools like `get_episode` and block destructive tools.

Your Buzzsprout API tokens and episode audio files are processed in an ephemeral V8 sandbox. Vinkius never stores your audio payloads, keeping your production assets secure.

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