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How to Use the Ghost MCP in Pydantic AI

Bring strict type safety to your Ghost CMS operations with Pydantic AI and runtime validation.

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Pydantic AI

Connect Ghost MCP to Pydantic AI

Create your Vinkius account to connect Ghost to Pydantic AI 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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Type-Safe Content Creation

The `create_post` tool requires a title and accepts optional HTML content to generate new articles. Pydantic AI validates these inputs against your exact schema before the request ever leaves your server. If the agent tries to send markdown instead of HTML, the framework fails loudly. You can set the post to publish immediately or leave it as a draft. The agent verifies the target publication by calling `get_site_settings` first. This guarantees your automation targets the correct production environment instead of a local testing instance.

Ghost MCP Server Member Tracking

Accessing your audience data happens through the `list_members` endpoint. The server returns subscriber emails, join dates, and account statuses. Because Pydantic AI enforces strict types, you never have to worry about silent data corruption in your analytics database. Your agent maps these users to specific plans using `list_membership_tiers`. It also checks `list_offers` to track active promotional campaigns. Every piece of revenue data gets validated at runtime, ensuring your downstream financial reporting remains perfectly accurate.

Site Structure Validation

Auditing your content starts with `list_posts` to gather metadata and IDs. The agent then calls `get_post_details` to inspect the full body of specific articles. It cross-references this content against your existing categories using `list_tags`. Static routing requires a separate check. The `list_pages` tool pulls down your non-blog content like the About or Contact sections. Finally, `list_newsletters` grabs your email configuration. You manage this entire read-only pipeline with any model you prefer, from local instances to Anthropic.

Setup guide

Set up Ghost MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install Pydantic AI with FastMCP

    Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.

  2. 2

    Configure the FastMCPToolset

    Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.

  3. 3

    Create and run your agent

    Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "ghost-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Ghost tools.",
)

result = await agent.run("List recent Ghost transactions")
print(result.output)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ghost. 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.

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Common questions about Ghost MCP in Pydantic AI

Grab the specific package using `pip install "pydantic-ai-slim[mcp]"`. Initialize the connection with `MCPToolset("http://...")`. Pass this directly to your agent via the `toolsets` parameter.
The framework is entirely model-agnostic. You can point it at OpenAI, Gemini, or a local Llama instance. The tools function identically regardless of the underlying LLM.
The framework throws a validation error immediately if an endpoint returns unexpected fields. When your agent calls `list_posts`, it expects a specific JSON structure. If that structure changes, the script halts instead of processing bad data.
Yes. The `list_pages` tool specifically targets non-blog content. This separates your core site architecture from your daily publishing feed.
This server exposes cleartext subscriber emails and join dates via the `list_members` tool. Vinkius isolates this execution inside a secure V8 environment. The connection is stateless, guaranteeing your customer information never writes to an intermediary disk.

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