How to Use the HubSpot CRM (Full) MCP in Pydantic AI

Q: Is setup for HubSpot CRM (Full) with Pydantic AI complicated?

No, it's very direct. You just instantiate an MCPToolset with the server URL and pass it to your agent's toolsets list. Pydantic AI handles the discovery and validation automatically from there.

Add type-safe HubSpot tools to your agent with Pydantic AI and get runtime validation on every CRM operation, preventing data corruption.

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Connect HubSpot CRM (Full) MCP to Pydantic AI

Create your Vinkius account to connect HubSpot CRM (Full) 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 CRM (Full) with Pydantic AI

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Perplexity

Create Records with Runtime Validation

When your agent uses `hs_create_contact` or `hs_create_deal`, the job isn't done until it gets a valid response. Pydantic AI ensures the JSON returned by the HubSpot API is parsed directly into a Pydantic model. If a field is missing or has the wrong type, your code will raise a `ValidationError` immediately. This means you can trust that a successful call to `hs_create_deal` actually returns a complete deal object with a valid ID. No more silent failures or agents hallucinating success. If it doesn't parse, it didn't work.

Search HubSpot with Type-Safe Results

Stop writing defensive code to handle weird API outputs. When your agent calls `hs_search_companies` or `hs_search_contacts`, Pydantic AI forces the results into clean, predictable Pydantic objects. You get exactly the fields you expect, every time. This is especially useful when an API changes. If a future HubSpot update adds or removes a field, you'll know instantly because the response will fail validation. Your agent won't pass corrupted or incomplete data downstream.

Build Reliable Workflows with this MCP Server

Chaining commands together is much safer when every step is validated. Your agent can call `hs_list_pipelines` to get pipeline IDs, and you know the result is a valid list of pipeline objects. It can then use an ID from that list to call `hs_create_deal`. After creating the deal, it can use the returned deal ID to add a follow-up with `hs_create_note`. At each stage of this sequence, Pydantic AI confirms the data integrity. This MCP Server gives you the tools, and Pydantic AI provides the safety net.

Setup guide

Set up HubSpot CRM (Full) 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-crm-full-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent HubSpot CRM (Full) transactions")
print(result.output)

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Common questions about HubSpot CRM (Full) MCP in Pydantic AI

Every tool in this MCP server has an associated Pydantic model for its output. When your agent gets a response from a tool like `hs_search_deals`, Pydantic AI automatically validates the raw JSON against that model. If it doesn't match, it raises an error.

Yes. Pydantic AI is model-agnostic. You can use it with OpenAI, Anthropic, Gemini, or a local model running on your own machine. The HubSpot CRM (Full) tools will work the same regardless of which LLM you choose.

No, it's very direct. You just instantiate an `MCPToolset` with the server URL and pass it to your agent's `toolsets` list. Pydantic AI handles the discovery and validation automatically from there.

The MCP server will return a proper error message from the HubSpot API. Pydantic AI will pass this error cleanly to your agent, so you can handle it in your code instead of guessing what went wrong.

This server processes HubSpot data like ticket subjects and engagement note contents. Each request runs in an isolated V8 sandbox that is destroyed after execution. Your credentials are encrypted and access is controlled by a single token, which you can revoke at any time.

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