SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Close MCP with Pydantic AI

Connect Pydantic AI to Close MCP. Create a new sales lead for acme corp, log an outbound call with follow-up notes, and more using natural language, with authentication handled for you.

Get started for freeGet a demo
Close logoClose
Api Key

Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools.

14 Tools45 Triggers

Introduction

This guide walks you through connecting Close to Pydantic AI using the Composio tool router. By the end, you'll have a working Close agent that can create leads and tasks, log calls and emails, send SMS messages, track opportunities, and review activities through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Close account through Composio's Close MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Close with

Claude CodeChatGPTClaude CoworkAntigravityOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Close
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Close workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the Close MCP server, and what's possible with it?

The Close MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Close account. It provides structured and secure access to your sales pipeline, so your agent can perform actions like creating leads, logging calls, sending SMS, managing tasks, and retrieving notes on your behalf.

  • Lead creation and management: Instantly create new leads with company details and contact information, keeping your CRM fresh and organized without manual entry.
  • Automated call logging: Have your agent log both inbound and outbound calls to specific leads, capturing call notes, durations, and recordings for seamless tracking.
  • SMS communication: Direct your agent to send or log SMS messages with leads, enabling timely follow-ups and improved client engagement.
  • Task management: Let your agent create tasks, set due dates, and track completion, making sure nothing slips through the cracks in your sales workflow.
  • Note retrieval and analysis: Fetch notes by lead or date, so your agent can summarize past interactions, surface important insights, or prepare for upcoming calls.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Close
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Close
  • MCPServerStreamableHTTP connects to the Close MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Close
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["close"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Close tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
close_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[close_mcp],
    instructions=(
        "You are a Close assistant. Use Close tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Close endpoint
  • The agent uses GPT-5 to interpret user commands and perform Close operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Close.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Close API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Close and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Close
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["close"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    close_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[close_mcp],
        instructions=(
            "You are a Close assistant. Use Close tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Close.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Close through Composio's Tool Router. With this setup, your agent can perform real Close actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Close for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS & TRIGGERS

Supported Tools and Triggers

Every Close action and event your agent gets out of the box.

Create Call

Creates a new call record in Close.

Create Email

Create or log a Close email activity.

Create Lead

Creates a new lead in Close CRM.

Create SMS Message

Create an SMS activity on a Close lead to log received, sent, or draft messages, or to send or schedule a message.

Create Task

Create a Close task associated with a lead, using task text and an actionable date, with optional completion status and assignment.

Delete Call

This tool allows you to delete a specific call activity in Close.

Get Contact

Retrieve one Close contact by ID, optionally limiting returned fields.

Get Notes

This tool retrieves a list of note activities from Close.

Get Opportunity

Retrieve one Close opportunity by ID with optional field projection.

List Activities

Lists one page of Close email or call activities using documented filters.

List Custom Activity Types

This tool lists the custom activity types defined in a Close organization, returning each type's id and name.

List Custom Object Types

This tool lists the custom object types defined in a Close organization, returning each type's id and name.

List Opportunities

List a page of Close opportunities with offset pagination.

Who Am I

Return the identity (email, name) of the connected Close account.

FRAMEWORKS

How to build Close MCP Agent with another framework

Claude Code logo

Claude Code

Use Close MCP with Claude Code

ChatGPT logo

ChatGPT

Use Close MCP with ChatGPT

Claude Cowork logo

Claude Cowork

Use Close MCP with Claude Cowork

Antigravity logo

Antigravity

Use Close MCP with Antigravity

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Close MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Close MCP with Claude Agent SDK

Codex logo

Codex

Use Close MCP with Codex

OpenClaw logo

OpenClaw

Use Close MCP with OpenClaw

Hermes logo

Hermes

Use Close MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Close MCP with Atomic Agent

Google ADK logo

Google ADK

Use Close MCP with Google ADK

LangChain logo

LangChain

Use Close MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Close MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Close MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Close MCP with LlamaIndex

CrewAI logo

CrewAI

Use Close MCP with CrewAI

AutoGen logo

AutoGen

Use Close MCP with AutoGen

FAQ

Frequently asked questions

With a standalone Close MCP server, the agents and LLMs can only access a fixed set of Close tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Close and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pydantic AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Close tools.

Yes, absolutely. You can configure which Close scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Close data and credentials are handled as safely as possible.

Start with Close.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Close tool your agent needs.Free to start.

Start building