How to Use the HubSpot CMS Hub MCP in Pydantic AI

Q: Can I use Pydantic AI to audit my HubSpot CMS Hub landing pages?

Absolutely. Call hslistlandingpages and the agent will receive a validated list of your conversion pages, ready for analysis.

Q: How do I search for blog posts in HubSpot CMS Hub with Pydantic AI?

Use hssearchblogposts within your agent toolset. The result will be a structured, type-checked list of articles matching your search criteria.

Bring type-safe HubSpot CMS Hub data into your Pydantic AI agent logic.

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Connect HubSpot CMS Hub MCP to Pydantic AI

Create your Vinkius account to connect HubSpot CMS Hub 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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Setup HubSpot CMS Hub with Pydantic AI

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Type-safe blog post retrieval

Pydantic AI validates every response from `hs_list_blog_posts` against your models. If the data isn't what you expected, the agent fails before it can make a mistake. Use `hs_get_blog_post` to get the full post details. Every field is checked at runtime to ensure your logic always has the correct data types.

Automate taxonomy audits

Your agent can call `hs_list_blog_tags` to verify your content categories. Since the output is validated, you never have to worry about silent data corruption. Use `hs_list_blog_authors` to map out your contributors. It gives your agent a reliable, type-checked list of authors for any content analysis task.

Validate pages and domains

Your agent can monitor your live site by querying `hs_list_site_pages`. Every page title and URL slug is validated for consistency. Run `hs_list_landing_pages` to verify your conversion assets. You can also use `hs_list_domains` to ensure your DNS configuration remains compliant with your expectations.

Setup guide

Set up HubSpot CMS Hub MCP in Pydantic AI

Prerequisites

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

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

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

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": {
        "hubspot-cms-hub-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent HubSpot CMS Hub transactions")
print(result.output)

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Common questions about HubSpot CMS Hub MCP in Pydantic AI

The MCP server sends the data, and Pydantic AI automatically checks it against your defined schema. Just call `hs_get_blog_post` and let the framework handle the validation.

Absolutely. Call `hs_list_landing_pages` and the agent will receive a validated list of your conversion pages, ready for analysis.

Use `hs_search_blog_posts` within your agent toolset. The result will be a structured, type-checked list of articles matching your search criteria.

No, the MCP server handles authentication internally. Your key never leaves your secure environment.

We use a managed V8 sandbox for all operations. Your landing page data is never logged or cached, ensuring total isolation between your CMS and the agent.

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