How to Use the Clearbit (HubSpot) MCP in Pydantic AI

Q: How do I configure Clearbit (HubSpot) for Pydantic AI?

Install pydantic-ai-slimmcp via pip. Initialize the connection using MCPToolset with your Vinkius HTTP endpoint. Assign that toolset to your agent using the toolsets array.

Connect Clearbit (HubSpot) to Pydantic AI to enforce strict type validation on every B2B data point your agent retrieves.

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Connect Clearbit (HubSpot) MCP to Pydantic AI

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

Ask AI about this MCP

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Claude

Perplexity

Enforce schema on Clearbit (HubSpot)

When your agent calls `find_company`, it expects a specific JSON structure back. Pydantic AI validates every single field returned from the MCP Server against your predefined Python models at runtime. If the API returns a string where an integer should be, the framework fails loudly. You catch bad data immediately instead of silently corrupting your CRM with hallucinated firmographics.

Extract prospects with type safety

Hand a target domain to your agent and watch it run `get_prospects` to pull a list of key contacts. The framework ensures every returned profile matches your exact user schema before passing it down the pipeline. If the agent needs to verify an individual, it triggers `find_person_and_company`. You get guaranteed, structured data for both the human and their employer, ready for immediate database insertion.

Audit traffic with an MCP Server

Pass a raw IP address into your agent so it can execute `reveal_ip` and identify the corporate network. The model then runs `find_risk` to calculate a fraud score for the visitor. Because Pydantic AI is model-agnostic, you can run this exact workflow using Anthropic, OpenAI, or a local Llama instance. The type guarantees remain identical regardless of which LLM processes the risk metrics.

Setup guide

Set up Clearbit (HubSpot) 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": {
        "clearbit-hubspot-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Clearbit (HubSpot) MCP in Pydantic AI

Install pydantic-ai-slim[mcp] via pip. Initialize the connection using MCPToolset with your Vinkius HTTP endpoint. Assign that toolset to your agent using the toolsets array.

It happens on every single request. The framework intercepts the raw JSON returned from endpoints like find_person. It runs that payload against your Pydantic schemas to ensure absolute type correctness before the agent proceeds.

Raw calls require manual error handling and parsing. This integration gives your agent direct access to tools like get_watchlist while guaranteeing the output matches your exact data models.

We host the integration in a zero-trust environment. You do not need to manage API keys or server deployments. Just grab your endpoint URL and start building.

The server processes personal emails, corporate domains, and IP addresses. Vinkius executes these requests inside an ephemeral V8 Isolate sandbox that is immediately destroyed after the response returns.

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