How to Use the WordPress Post Drafter MCP in Google ADK

Integrate WordPress Post Drafter with Google ADK for enterprise content workflow automation.

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Connect WordPress Post Drafter MCP to Google ADK

Create your Vinkius account to connect WordPress Post Drafter 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 WordPress Post Drafter with Google ADK

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Drafting Content into BigQuery Workflows

The `create_wordpress_draft` tool takes AI-generated title and content and saves it as a Draft post in WordPress. You run this through the Google ADK, linking your content generation to existing data sources. This capability lets you act on massive datasets that already live in BigQuery before drafting any final content.

Using `create_wordpress_draft` with Long Context

The tool uses the input title and content to create a WordPress Draft. Since Google ADK supports models holding 1M+ tokens, you can feed enormous amounts of source material into your agent. This means the drafted posts are based on deep analysis of complex documents or large data exports.

Executing MCP Server Actions via Vertex AI

You pass this tool to your LlmAgent, making it available for action. When triggered, `create_wordpress_draft` saves the post as a Draft using the provided title and body text. This keeps all content creation actions managed within your Google Cloud infrastructure.

Setup guide

Set up WordPress Post Drafter 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 WordPress Post Drafter 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="WordPress Post Drafter_agent",
    model="gemini-2.0-flash",
    instruction="You have access to WordPress Post Drafter tools via MCP.",
    tools=mcp_tools,
)

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Common questions about WordPress Post Drafter MCP in Google ADK

You incorporate the MCP Server into your LlmAgent setup. The agent then uses `create_wordpress_draft` when it determines content needs to be saved as a Draft.

Absolutely not. When the tool runs, the post is strictly saved as a Draft in WordPress, ensuring that nothing goes live without manual review.

The server handles string data for both the title and the content. The body can be provided as plain text or HTML format.

You treat it like any other toolset, passing it to your LlmAgent. This allows you to connect content generation directly to BigQuery data sources.

The server only touches text data: the post title and the post body content. You manage this within your secure Google Cloud environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.