Where do I find my Cloze API key?

You can generate an API key in the Cloze web app. Go to Settings > Accounts and Services, and click the 'API Key' section to add a new token.

Which email address should I use for authentication?

Use the exact primary email address registered to your active Cloze account.

Can I manage custom fields with this server?

Yes, you can retrieve custom field definitions and command the agent to set specific values when creating or updating contacts.

Cloze MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: Cloze
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Cloze through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Cloze "
            "(9 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Cloze?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Cloze MCP Server

Cloze is a smart CRM that automatically tracks your interactions and provides AI-powered insights to manage your relationships, projects, and deals. Through this MCP server, your AI agent can effortlessly pull contact histories, lookup custom tags, verify relationship strengths, and update ongoing project states without breaking your workflow.

Pydantic AI validates every Cloze tool response against typed schemas, catching data inconsistencies at build time. Connect 9 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

The Cloze MCP Server exposes 9 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Cloze to Pydantic AI via MCP

Follow these steps to integrate the Cloze MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 9 tools from Cloze with type-safe schemas

Why Use Pydantic AI with the Cloze MCP Server

Pydantic AI provides unique advantages when paired with Cloze through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Cloze integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Cloze connection logic from agent behavior for testable, maintainable code

Cloze + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Cloze MCP Server delivers measurable value.

Type-safe data pipelines: query Cloze with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Cloze tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Cloze and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Cloze responses and write comprehensive agent tests

Cloze MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect Cloze to Pydantic AI via MCP:

create_person

Provide at least name or email. Create a new person in Cloze

create_project

Create a new project, deal, or property in Cloze

get_person

Retrieve detailed information about a specific person by email

list_companies

Retrieve a list of companies from Cloze

list_custom_fields

Retrieve definitions for custom fields in your Cloze account

list_people

Retrieve a list of people (contacts) from Cloze

list_projects

Retrieve a list of projects, properties, or deals from Cloze

search_people_by_tag

Find contacts that have a specific tag

update_person

Email is used as the match key. Update an existing person in Cloze (matching by email)

Example Prompts for Cloze in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Cloze immediately.

"Get all details for the person with email 'sarah@example.com' in Cloze."

"Show me my active projects in Cloze."

"Find all contacts tagged with 'VIP' in Cloze."

Troubleshooting Cloze MCP Server with Pydantic AI

Common issues when connecting Cloze to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Cloze + Pydantic AI FAQ

Common questions about integrating Cloze MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Cloze MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.