How to Use the Cloze MCP in Pydantic AI

Q: How do I connect the Cloze MCP Server to a Pydantic AI agent?

Install the library with the MCP extra, then initialize MCPToolset with your Vinkius HTTP URL. Pass this toolset into the toolsets argument when building your Pydantic AI agent to expose Cloze tools.

Q: Can my agent create new Cloze records safely?

Yes, the agent can call createperson with strict type validation on the email and name fields. This prevents your Pydantic AI agent from pushing malformed contacts to your CRM.

Build type-safe Python agents that validate Cloze CRM data at runtime with Pydantic AI.

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Connect Cloze MCP to Pydantic AI

Create your Vinkius account to connect Cloze 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 Cloze with Pydantic AI

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Validate Cloze Contacts in Pydantic AI

When your agent fetches data from your Cloze account, you need to be sure it matches your Python schemas. This MCP Server lets your Pydantic AI agent call `get_person` or `list_people` and validates the response against strict type definitions at runtime. If Cloze returns an unexpected field format, the Pydantic AI framework raises a validation error immediately. You avoid corrupted contact records from breaking your downstream application logic.

Type-Safe Project and Deal Management

Managing your Cloze pipeline requires absolute accuracy when creating deals. By exposing `create_project` and `list_projects` via MCP to Pydantic AI, your agent can write back to your CRM with guaranteed schema compliance. The Pydantic AI framework ensures that every deal name, property value, or custom status field matches your expected Pydantic models. You will never have to worry about silent API failures or half-written records in Cloze.

Schema-Enforced Contact Tagging

Your agents can search and filter your Cloze network using `search_people_by_tag` and `list_companies`. Pydantic AI parses these payloads and ensures the tags and company details fit your strict application types. If you modify your Cloze structure, calling `list_custom_fields` lets the agent adapt to the new layout. This keeps your type-safe agent working even when your Cloze account configuration changes.

Setup guide

Set up Cloze 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": {
        "cloze-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Cloze MCP in Pydantic AI

Install the library with the MCP extra, then initialize `MCPToolset` with your Vinkius HTTP URL. Pass this toolset into the `toolsets` argument when building your Pydantic AI agent to expose Cloze tools.

The Pydantic AI agent will raise a validation error, allowing you to catch the structure mismatch early. You can use `list_custom_fields` to inspect the actual CRM schema and update your Pydantic models.

Yes, the Pydantic AI framework supports both Streamable HTTP and SSE transports. This allows your agent to connect to the hosted MCP endpoint reliably.

Yes, the agent can call `create_person` with strict type validation on the email and name fields. This prevents your Pydantic AI agent from pushing malformed contacts to your CRM.

Your customer contacts, project files, and company records are processed in memory and validated locally. The Vinkius sandbox ensures that your Cloze API keys are never exposed directly to the LLM or stored in plain text.

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