How to Use the Tumblr MCP in Google ADK

Q: Can I use the Google ADK to list posts from a Tumblr blog?

Yes, simply call listblogposts. The Google ADK is built for enterprise data flow, so it handles high-volume retrieval of Tumblr content and gets it ready for BigQuery insertion.

Q: How does the Google ADK handle searching across multiple Tumblr tags?

You use listtaggedposts to search by specific tags. Because you're operating in a Google Cloud environment, your agent can process these searches and write the results directly into structured tables.

Q: What if I need an avatar URL for a Tumblr blog using the Google ADK?

You call getblogavatar. This tool retrieves the necessary unique identifier, which your agent then uses to enrich records across multiple data sources in BigQuery.

Q: What is the best way to get detailed post information from Tumblr with the Google ADK?

Use getpost. This fetches comprehensive details for a single entry. The Gemini models powering the Google ADK are great at interpreting and holding context across this rich, structured data.

Move Tumblr data streams directly into BigQuery using the Google ADK.

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Connect Tumblr MCP to Google ADK

Create your Vinkius account to connect Tumblr 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 Tumblr with Google ADK

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Collect post details from Tumblr for BigQuery

Need historical records? Use `get_post` to pull all specific details about a single Tumblr entry. This structured data is ideal because it can be directly ingested into your BigQuery tables. The Google ADK supports long-context reasoning, meaning your agent can process the metadata gathered from hundreds of posts in one go.

Bulk list blog posts using the MCP Server

If you're building a data warehouse around Tumblr activity, `list_blog_posts` is what you need. It pulls multiple post records for an entire stream. The ADK handles this high volume of data flow efficiently. This makes it simple to build ETL pipelines that continuously feed fresh content from Tumblr into Google Cloud infrastructure.

Get unique blog identifiers with the MCP Server

Use `get_blog_avatar` to get a consistent identifier for any given Tumblr blog. This avatar URL serves as an excellent primary key when you join data sets in BigQuery. The ability to retrieve this basic info ensures your agent has accurate cross-referencing data before it attempts more complex operations.

Setup guide

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

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Common questions about Tumblr MCP in Google ADK

Yes, simply call `list_blog_posts`. The Google ADK is built for enterprise data flow, so it handles high-volume retrieval of Tumblr content and gets it ready for BigQuery insertion.

You use `list_tagged_posts` to search by specific tags. Because you're operating in a Google Cloud environment, your agent can process these searches and write the results directly into structured tables.

You call `get_blog_avatar`. This tool retrieves the necessary unique identifier, which your agent then uses to enrich records across multiple data sources in BigQuery.

Use `get_post`. This fetches comprehensive details for a single entry. The Gemini models powering the Google ADK are great at interpreting and holding context across this rich, structured data.

The entire framework is designed for that. By connecting through the MCP Server via `list_blog_posts`, you guarantee that every piece of data follows established Google Cloud best practices.

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