How to Use the Udemy MCP in Google ADK

Q: How do I get course details from Udemy using Google ADK?

You call the courses tool with a specific ID. This gives you all the metadata needed to index or analyze that single class within your Google Cloud data structure.

Q: Can I analyze all instructor feedback from Udemy using Google ADK?

Yes. The instructorreviews tool collects reviews for every course taught, giving you the volume needed to run comprehensive analysis across your enterprise data lake.

Q: Does this MCP Server handle messaging details on Udemy using Google ADK?

It does. You use instructormessages to pull all direct messages for the authenticated instructor, allowing you to process private feedback alongside public course material.

Q: Is the data privacy handled when connecting with Udemy and Google ADK?

The server touches user-generated content, specifically instructormessages, which are direct communications. Ensure your agent adheres strictly to all relevant privacy policies.

Process Udemy course data and feedback using Google ADK enterprise agents.

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Connect Udemy MCP to Google ADK

Create your Vinkius account to connect Udemy 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 Udemy with Google ADK

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Retrieve All Courses Taught by an Instructor

The `instructor_courses` tool lists every class taught by the authenticated instructor. This is essential for building a complete profile of expertise that feeds directly into BigQuery or Vertex AI. You get all necessary IDs to then pull details, making it easy to scope out a full body of work.

Gather Course Reviews and Feedback Data

Use `course_reviews` when you need reviews for one specific course ID. This tool lets your agent gather raw feedback data that can be loaded into Google Cloud infrastructure. If you want a broader view, the `instructor_reviews` tool aggregates all reviews across every class taught by the instructor.

Access Instructor Q&A and Messages

The `instructor_qa` tool retrieves QA questions from all courses associated with the instructor. This data is excellent for training models on common student inquiries. It also pulls private communications using `instructor_messages`, giving your agent a full view of direct feedback.

Setup guide

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

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Common questions about Udemy MCP in Google ADK

You call the `courses` tool with a specific ID. This gives you all the metadata needed to index or analyze that single class within your Google Cloud data structure.

It provides course IDs, reviews, QA records, message logs, and full metadata. All the content is ready to be processed by Gemini models in a long-context environment.

Yes. The `instructor_reviews` tool collects reviews for every course taught, giving you the volume needed to run comprehensive analysis across your enterprise data lake.

It does. You use `instructor_messages` to pull all direct messages for the authenticated instructor, allowing you to process private feedback alongside public course material.

The server touches user-generated content, specifically `instructor_messages`, which are direct communications. Ensure your agent adheres strictly to all relevant privacy policies.

Use it with your favorite AI tools

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