How to integrate Clientary MCP with Pydantic AI

This guide walks you through connecting Clientary to Pydantic AI using the Composio tool router. By the end, you'll have a working Clientary agent that can create new invoice for a client, list all active projects this month, send payment reminder to overdue clients through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Clientary account through Composio's Clientary MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Clientary

Api Key

Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.

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Introduction

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

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

Also integrate Clientary with

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

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 Clientary
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 Clientary 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 Clientary MCP server, and what's possible with it?

The Clientary MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Clientary account. It provides structured and secure access so your agent can perform Clientary operations on your behalf.

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:

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

Step-by-step Guide

Step by step09 STEPS

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

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.

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 Clientary
pydantic-ai lets you create structured AI agents with tool support
python-dotenv loads your environment variables securely from a .env file

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

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 Clientary
MCPServerStreamableHTTP connects to the Clientary MCP server endpoint
Agent from Pydantic AI lets you define and run the AI assistant

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 Clientary
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["clientary"],
    )
    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 Clientary 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

Initialize the Pydantic AI Agent

python

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

What's happening:

The MCP client connects to the Clientary endpoint
The agent uses GPT-5 to interpret user commands and perform Clientary operations
The instructions field defines the agent's role and behavior

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 Clientary.\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
Clientary API calls happen automatically under the hood
The model keeps conversation history to maintain context across turns

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 Clientary 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 Clientary
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["clientary"],
    )
    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
    clientary_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[clientary_mcp],
        instructions=(
            "You are a Clientary assistant. Use Clientary 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 Clientary.\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 Clientary through Composio's Tool Router. With this setup, your agent can perform real Clientary 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 + Clientary 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

Supported Tools

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

Create Client

Tool to create a new client record in Clientary.

Create Contact

Tool to create a new contact within a specified client.

Create Expense

Tool to create a new expense record in Clientary to track expenditures within your account.

Create Lead

Tool to create a new lead record in Clientary.

Create Project

Tool to create a new project in Clientary with name and rate.

Create Task

Tool to create a new task in Clientary.

Delete Client

Tool to remove a client and all associated projects, invoices, estimates, and contacts.

Delete Lead

Tool to permanently delete a lead and all associated Estimates and Contacts.

Delete Payment

Tool to remove an existing payment from an invoice.

Delete Payment Profile

Tool to remove a specific payment profile from a client's account.

Delete Recurring Schedule

Tool to remove a recurring schedule by its identifier.

Get Client

Tool to fetch details for a specific client using its ID.

Get Contact

Tool to retrieve a single contact by its ID.

Get Estimate

Tool to retrieve details for a single estimate by ID.

Get Expense

Tool to retrieve details for a single expense record in Clientary.

Get Hour Entry

Tool to obtain details about a specific time entry in Clientary.

Get Invoice

Tool to retrieve detailed information for a specific invoice by ID.

Get Lead

Tool to retrieve a single lead by its ID.

Get Project

Tool to retrieve a single project by its identifier.

Get Staff

Tool to retrieve a single staff member by their ID.

Get Task

Tool to retrieve a specific task by its ID.

List Client Contacts

Tool to retrieve all contacts for a specific client with pagination support.

List Client Expenses

Tool to retrieve all expenses for a specific client within an optional date range.

List Client Invoices

Tool to retrieve all invoices for a specific client with pagination support (30 results per page).

List Client Projects

Tool to retrieve all projects associated with a specific client with pagination support (10 results per page).

List Clients

Tool to retrieve all clients with pagination support (10 results per page).

List Expenses

Tool to retrieve expenses by date range (defaults to current fiscal year).

List Leads

Tool to retrieve all leads with pagination support.

List Payments

Tool to retrieve all payments with pagination support (30 results per page).

List Project Estimates

Tool to retrieve estimates scoped to a particular project with pagination support (30 results per page).

List Project Expenses

Tool to retrieve all expenses for a specific project within an optional date range.

List Project Hours

Tool to retrieve all time tracking entries logged against a specific project.

List Project Invoices

Tool to retrieve all invoices linked to a specific project with pagination support (30 results per page).

List Projects

Tool to retrieve all projects with pagination support (10 results per page).

List Staff

Tool to retrieve all staff members for an account.

List Tasks

Tool to retrieve all tasks with pagination support (50 results per page).

Send Invoice Message

Tool to send an invoice message to recipients via email.

Update Client

Tool to update an existing client record in Clientary with partial or complete field modifications.

Update Expense

Tool to update an existing expense record in Clientary with partial or complete field modifications.

Update Hour Entry

Tool to modify an existing time entry in Clientary with partial or complete field updates.

Update Project

Tool to update an existing project in Clientary with partial or complete field modifications.

Update Task

Tool to update an existing task in Clientary with partial or complete field modifications.

FRAMEWORKS

How to build Clientary MCP Agent with another framework

ChatGPT

Use Clientary MCP with ChatGPT

OpenAI Agents SDK

Use Clientary MCP with OpenAI Agents SDK

Claude Agent SDK

Use Clientary MCP with Claude Agent SDK

Claude Code

Use Clientary MCP with Claude Code

Claude Cowork

Use Clientary MCP with Claude Cowork

Codex

Use Clientary MCP with Codex

Cursor

Use Clientary MCP with Cursor

OpenClaw

Use Clientary MCP with OpenClaw

Hermes

Use Clientary MCP with Hermes

CLI

Use Clientary MCP with CLI

Google ADK

Use Clientary MCP with Google ADK

LangChain

Use Clientary MCP with LangChain

Vercel AI SDK

Use Clientary MCP with Vercel AI SDK

Mastra AI

Use Clientary MCP with Mastra AI

LlamaIndex

Use Clientary MCP with LlamaIndex

CrewAI

Use Clientary MCP with CrewAI

OpenCode

Use Clientary MCP with OpenCode

VS Code

Use Clientary MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Google Sheets

Oauth2

Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.

Notion

Oauth2Api Key

Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

Airtable

Oauth2Api Key

Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.

Hubspot

Oauth2Api Key

HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place.

FAQ

Frequently asked questions

With a standalone Clientary MCP server, the agents and LLMs can only access a fixed set of Clientary tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Clientary 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 Clientary tools.

Yes, absolutely. You can configure which Clientary 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 Clientary data and credentials are handled as safely as possible.

Start with Clientary.It takes 30 seconds.

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

Start building

Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Clientary MCP with Pydantic AI

Connect Clientary without auth hassles

Introduction

Also integrate Clientary with

TL;DR

What is Pydantic AI?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Tool Router Session

Initialize the Pydantic AI Agent

Build the chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Clientary MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Google Sheets

Notion

Airtable

Hubspot

Frequently asked questions

What are the differences in Tool Router MCP and Clientary MCP?+

Can I use Tool Router MCP with Pydantic AI?+

Can I manage the permissions and scopes for Clientary while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Clientary.It takes 30 seconds.

Teams ship real agents on Composio