How to Use the Wistia MCP in Google ADK

Q: How do I get a full list of my Wistia projects using Google ADK?

The agent executes listprojects. This provides a straightforward inventory of all your current and past projects. You can then feed this list into BigQuery for advanced modeling.

Q: What kinds of performance metrics are available with Wistia and Google ADK?

You get comprehensive stats through getvideostats and overall account data via getaccountanalytics. These structured results integrate perfectly into the Gemini ecosystem.

Q: Can I programmatically modify video information with Wistia and Google ADK?

Yes. The agent uses updatevideodetails to modify metadata on a video asset. This lets your production pipeline keep content descriptions accurate without manual intervention.

Q: Do I need to worry about listing all videos when using Wistia and Google ADK?

The listvideos tool is how you get a clean manifest of every media asset. This list serves as the starting point for almost any deeper analysis or operation.

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Connect Wistia MCP to Google ADK

Create your Vinkius account to connect Wistia 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 Wistia with Google ADK

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Analyze account performance with the MCP Server

The agent pulls overall site metrics using `get_account_analytics`. Since you're building on Google Cloud, this data streams directly into your BigQuery models. It’s instant, reliable reporting. Need to scope down the data? You can first list all assets with `list_videos`, and then pull specific analytics for any video using `get_video_stats`.

Manage project metadata in Google ADK

When you need a new initiative tracked, the agent calls `create_project`. This isn't just tracking; it lets your agents build structured records of development projects. You can also review existing work by listing them with `list_projects`. If details get messy, use `get_project_details` to pull verified metadata for any given project.

Extract detailed video and caption information

The agent gets deep insights into a specific asset using `get_video_details`. You're not just getting basic info; you get structured data ready for Vertex AI processing. Separately, it can list all associated captions via `list_video_captions`. This capability is key when your agents need to cross-reference spoken content with video metadata.

Setup guide

Set up Wistia 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 Wistia 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="Wistia_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Wistia tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Wistia MCP in Google ADK

The agent executes `list_projects`. This provides a straightforward inventory of all your current and past projects. You can then feed this list into BigQuery for advanced modeling.

You get comprehensive stats through `get_video_stats` and overall account data via `get_account_analytics`. These structured results integrate perfectly into the Gemini ecosystem.

Yes. The agent uses `update_video_details` to modify metadata on a video asset. This lets your production pipeline keep content descriptions accurate without manual intervention.

The `list_videos` tool is how you get a clean manifest of every media asset. This list serves as the starting point for almost any deeper analysis or operation.

The server touches video metadata, project details, account analytics, and video performance statistics. It's all structured information about your content assets and associated usage metrics.

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