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Close MCP Server for Pydantic AIGive Pydantic AI instant access to 6 tools to Create Lead, Get Current User, Get Lead Details, and more

Built by Vinkius GDPR 6 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The Close app connector for Pydantic AI is a standout in the Communication Messaging category — giving your AI agent 6 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Close "
            "(6 tools)."
        ),
    )

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

asyncio.run(main())
Close
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About Close MCP Server

Connect your Close CRM account to any AI agent and take full control of your sales workflows through natural conversation.

Pydantic AI validates every Close tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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.

What you can do

  • Lead Management — List all leads in your pipeline and retrieve full company profiles with contacts, custom fields, and activity history
  • Lead Creation — Add new leads directly from conversation, including company name and website URL
  • Opportunity Tracking — Monitor your active deals with stage, value, and expected close dates
  • Task Management — Review pending and completed CRM tasks to stay on top of follow-ups
  • User Context — Retrieve your authenticated user profile to understand your current permissions and role

The Close MCP Server exposes 6 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.

All 6 Close tools available for Pydantic AI

When Pydantic AI connects to Close through Vinkius, your AI agent gets direct access to every tool listed below — spanning lead-management, pipeline-tracking, inside-sales, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_lead

Create a new lead

get_current_user

Get information about the authenticated API user

get_lead_details

Get details of a specific lead

list_crm_tasks

List CRM tasks

list_leads

List all leads in Close CRM

list_opportunities

List sales opportunities

Connect Close to Pydantic AI via MCP

Follow these steps to wire Close into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 6 tools from Close with type-safe schemas

Why Use Pydantic AI with the Close MCP Server

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

01

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

02

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

03

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

04

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

Close + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Close in Pydantic AI

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

01

"List all my leads in Close and highlight the ones added this week."

02

"Create a new lead for the company 'Nordic AI Labs' with their website nordicailabs.com."

03

"Show my active sales opportunities and any overdue tasks I need to handle."

Troubleshooting Close MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Close + Pydantic AI FAQ

Common questions about integrating Close MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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