Can I see my open opportunities through the agent?

Yes! Use the `list_close_opportunities` tool. The agent will return all deals, and you can ask it to filter for those in an 'Open' or specific pipeline stage.

How do I check the tasks due for today?

Use the `list_close_tasks` tool. Your agent will fetch the list of CRM tasks, and you can ask it to identify those with a due date of today.

Where do I find my Close API Key?

Log in to Close, go to **Settings**, and select **API Keys**. You can generate and copy a new API key from that section.

Close MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Close
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 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.

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 Close "
            "(8 tools)."
        ),
    )

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

Connect your Close CRM account to any AI agent and take full control of your sales automation through natural conversation. Streamline how you manage leads, deals, and daily to-dos natively.

Pydantic AI validates every Close tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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 Oversight — List and retrieve details for all leads (companies) including status and contact info natively
Opportunity Intelligence — Access and monitor sales deals and their values across different pipelines flawlessly
Task Management — List and review CRM tasks and reminders to stay on top of your follow-ups securely
Pipeline Logistics — Monitor sales pipelines and understand where deals are in the funnel flawlessly
Status Tracking — List available stages for leads and opportunities to maintain clean data flawlessly
User Visibility — Access your own profile and core CRM metadata directly within your workspace flawlessly

The Close MCP Server exposes 8 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 Close to Pydantic AI via MCP

Follow these steps to integrate the Close 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 8 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.

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 Close integration code

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

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.

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

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

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

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

Close MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Close to Pydantic AI via MCP:

get_lead_details

Get detailed information for a specific lead

get_my_close_profile

Retrieve information about the authenticated user

get_opportunity_details

Get detailed information for a specific opportunity

list_close_leads

List all leads in Close CRM

list_close_opportunities

List all sales opportunities

list_close_pipelines

List sales pipelines configured in the account

list_close_tasks

List CRM tasks and reminders

list_lead_statuses

List available stages/statuses for leads

Example Prompts for Close in Pydantic AI

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

"List my last 5 leads in Close."

"Show me the value of my current sales pipeline."

"What are my pending tasks for this week?"

Troubleshooting Close MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Close + Pydantic AI FAQ

Common questions about integrating Close 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 Close MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.