# How to integrate Clientary MCP with Pydantic AI ```json { "title": "How to integrate Clientary MCP with Pydantic AI", "toolkit": "Clientary", "toolkit_slug": "clientary", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/clientary/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/clientary/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:27:37.976Z" } ``` ## Introduction 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. ## Also integrate Clientary with - [ChatGPT](https://composio.dev/toolkits/clientary/framework/chatgpt) - [Antigravity](https://composio.dev/toolkits/clientary/framework/antigravity) - [OpenAI Agents SDK](https://composio.dev/toolkits/clientary/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/clientary/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/clientary/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/clientary/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/clientary/framework/codex) - [Cursor](https://composio.dev/toolkits/clientary/framework/cursor) - [VS Code](https://composio.dev/toolkits/clientary/framework/vscode) - [OpenCode](https://composio.dev/toolkits/clientary/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/clientary/framework/openclaw) - [Hermes](https://composio.dev/toolkits/clientary/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/clientary/framework/cli) - [Google ADK](https://composio.dev/toolkits/clientary/framework/google-adk) - [LangChain](https://composio.dev/toolkits/clientary/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/clientary/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/clientary/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/clientary/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/clientary/framework/crew-ai) ## 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. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `CLIENTARY_CREATE_CLIENT` | Create Client | Tool to create a new client record in Clientary. Use when you need to add a new client to the system with company details and contact information. | | `CLIENTARY_CREATE_CONTACT` | Create Contact | Tool to create a new contact within a specified client. Use when you need to add a contact to a client account with name and email as required fields. | | `CLIENTARY_CREATE_EXPENSE` | Create Expense | Tool to create a new expense record in Clientary to track expenditures within your account. Use when you need to record expenses, optionally assigning them to specific clients or projects. Requires an amount field. | | `CLIENTARY_CREATE_LEAD` | Create Lead | Tool to create a new lead record in Clientary. Use when you need to add a new lead to the system with company details and contact information. | | `CLIENTARY_CREATE_PROJECT` | Create Project | Tool to create a new project in Clientary with name and rate. Use when you need to set up a new project for tracking time, expenses, or managing client work. | | `CLIENTARY_CREATE_TASK` | Create Task | Tool to create a new task in Clientary. Use when you need to create a task with a title, optionally associating it with a project and assignee. | | `CLIENTARY_DELETE_CLIENT` | Delete Client | Tool to remove a client and all associated projects, invoices, estimates, and contacts. Use when you need to permanently delete a client from Clientary. WARNING: Deletions are permanent and not reversible. | | `CLIENTARY_DELETE_LEAD` | Delete Lead | Tool to permanently delete a lead and all associated Estimates and Contacts. Use when you need to remove a lead that is no longer needed. Warning: This action is irreversible. | | `CLIENTARY_DELETE_PAYMENT` | Delete Payment | Tool to remove an existing payment from an invoice. Use when you need to permanently delete a payment record. WARNING: Deletions are permanent and not reversible. | | `CLIENTARY_DELETE_PAYMENT_PROFILE` | Delete Payment Profile | Tool to remove a specific payment profile from a client's account. Use when you need to delete a payment profile. Note: Client must have an active payment integration with Stripe to manage payment profiles. | | `CLIENTARY_DELETE_RECURRING_SCHEDULE` | Delete Recurring Schedule | Tool to remove a recurring schedule by its identifier. Use when you need to permanently delete a recurring schedule from Clientary. Once deleted, the recurring schedule will no longer generate periodic invoices. | | `CLIENTARY_GET_CLIENT` | Get Client | Tool to fetch details for a specific client using its ID. Use when you need to retrieve complete information about a client from Clientary. | | `CLIENTARY_GET_CONTACT` | Get Contact | Tool to retrieve a single contact by its ID. Use when you need to fetch detailed information about a specific contact from Clientary. | | `CLIENTARY_GET_ESTIMATE` | Get Estimate | Tool to retrieve details for a single estimate by ID. Use when you need to obtain comprehensive estimate information including line items, tax details, and financial data. | | `CLIENTARY_GET_EXPENSE` | Get Expense | Tool to retrieve details for a single expense record in Clientary. Use when you need to get specific information about an expense by its unique identifier. | | `CLIENTARY_GET_HOUR_ENTRY` | Get Hour Entry | Tool to obtain details about a specific time entry in Clientary. Use when you need to retrieve information about a logged hour entry by its unique identifier. | | `CLIENTARY_GET_INVOICE` | Get Invoice | Tool to retrieve detailed information for a specific invoice by ID. Use when you need to fetch invoice details including line items, payments, tax information, and current status. | | `CLIENTARY_GET_LEAD` | Get Lead | Tool to retrieve a single lead by its ID. Use when you need to fetch detailed information about a specific lead from Clientary. | | `CLIENTARY_GET_PROJECT` | Get Project | Tool to retrieve a single project by its identifier. Use when you need to fetch detailed information about a specific project in Clientary. | | `CLIENTARY_GET_STAFF` | Get Staff | Tool to retrieve a single staff member by their ID. Use when you need to fetch detailed information about a specific staff member from Clientary. | | `CLIENTARY_GET_TASK` | Get Task | Tool to retrieve a specific task by its ID. Use when you need to fetch detailed information about a task from Clientary. | | `CLIENTARY_LIST_CLIENT_CONTACTS` | List Client Contacts | Tool to retrieve all contacts for a specific client with pagination support. Use when you need to fetch the list of contacts associated with a particular client in Clientary. | | `CLIENTARY_LIST_CLIENT_EXPENSES` | List Client Expenses | Tool to retrieve all expenses for a specific client within an optional date range. Use when you need to fetch expense records associated with a particular client from Clientary. | | `CLIENTARY_LIST_CLIENT_INVOICES` | List Client Invoices | Tool to retrieve all invoices for a specific client with pagination support (30 results per page). Use when you need to fetch invoices associated with a particular client from Clientary. | | `CLIENTARY_LIST_CLIENT_PROJECTS` | List Client Projects | Tool to retrieve all projects associated with a specific client with pagination support (10 results per page). Use when you need to fetch projects for a particular client from Clientary. | | `CLIENTARY_LIST_CLIENTS` | List Clients | Tool to retrieve all clients with pagination support (10 results per page). Use when you need to fetch a list of clients from Clientary with optional filtering by modification date or custom sorting. | | `CLIENTARY_LIST_EXPENSES` | List Expenses | Tool to retrieve expenses by date range (defaults to current fiscal year). Use when you need to fetch a list of expenses from Clientary with optional filtering by start and end dates. | | `CLIENTARY_LIST_LEADS` | List Leads | Tool to retrieve all leads with pagination support. Use when you need to fetch a list of leads from Clientary with optional sorting by name or date. | | `CLIENTARY_LIST_PAYMENTS` | List Payments | Tool to retrieve all payments with pagination support (30 results per page). Use when you need to fetch a list of payments from Clientary with optional pagination and custom sorting. | | `CLIENTARY_LIST_PROJECT_ESTIMATES` | List Project Estimates | Tool to retrieve estimates scoped to a particular project with pagination support (30 results per page). Use when you need to fetch all estimates associated with a specific project. | | `CLIENTARY_LIST_PROJECT_EXPENSES` | List Project Expenses | Tool to retrieve all expenses for a specific project within an optional date range. Use when you need to fetch expense records associated with a particular project from Clientary. | | `CLIENTARY_LIST_PROJECT_HOURS` | List Project Hours | Tool to retrieve all time tracking entries logged against a specific project. Use when you need to fetch hour entries for a particular project, optionally filtering by billed or unbilled status. | | `CLIENTARY_LIST_PROJECT_INVOICES` | List Project Invoices | Tool to retrieve all invoices linked to a specific project with pagination support (30 results per page). Use when you need to fetch invoices associated with a particular project from Clientary. | | `CLIENTARY_LIST_PROJECTS` | List Projects | Tool to retrieve all projects with pagination support (10 results per page). Use when you need to fetch a list of projects from Clientary with optional filtering for closed projects. | | `CLIENTARY_LIST_STAFF` | List Staff | Tool to retrieve all staff members for an account. Use when you need to fetch a complete list of staff members from Clientary. | | `CLIENTARY_LIST_TASKS` | List Tasks | Tool to retrieve all tasks with pagination support (50 results per page). Use when you need to fetch a list of tasks from Clientary. | | `CLIENTARY_SEND_INVOICE_MESSAGE` | Send Invoice Message | Tool to send an invoice message to recipients via email. Use when you need to email an invoice to clients with customizable subject, message content, and options to send a copy to yourself or attach a PDF. | | `CLIENTARY_UPDATE_CLIENT` | Update Client | Tool to update an existing client record in Clientary with partial or complete field modifications. Use when you need to modify client details such as name, address, description, or custom fields. All fields except ID are optional. | | `CLIENTARY_UPDATE_EXPENSE` | Update Expense | Tool to update an existing expense record in Clientary with partial or complete field modifications. Use when you need to modify expense details such as amount, description, client assignment, project assignment, or incurred date. All fields except ID are optional. | | `CLIENTARY_UPDATE_HOUR_ENTRY` | Update Hour Entry | Tool to modify an existing time entry in Clientary with partial or complete field updates. Use when you need to update hours, title, date, description, rate, or billing status of a logged hour entry. | | `CLIENTARY_UPDATE_PROJECT` | Update Project | Tool to update an existing project in Clientary with partial or complete field modifications. Use when you need to modify project details such as name, rate, description, budget, status, or other project attributes. All fields except ID are optional - only provided fields will be updated. | | `CLIENTARY_UPDATE_TASK` | Update Task | Tool to update an existing task in Clientary with partial or complete field modifications. Use when you need to modify task details such as title, description, completion status, assignee, or due date. All fields except ID are optional. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Clientary MCP server is an implementation of the Model Context Protocol that connects your AI agent to Clientary. It provides structured and secure access so your agent can perform Clientary operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 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 ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies 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 ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables 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 ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies 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 ```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() ``` ### 5. Create a Tool Router Session 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 ```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") ``` ### 6. Initialize the Pydantic AI Agent 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 ```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." ), ) ``` ### 7. Build the chat interface 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 ```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() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```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. ## How to build Clientary MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/clientary/framework/chatgpt) - [Antigravity](https://composio.dev/toolkits/clientary/framework/antigravity) - [OpenAI Agents SDK](https://composio.dev/toolkits/clientary/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/clientary/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/clientary/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/clientary/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/clientary/framework/codex) - [Cursor](https://composio.dev/toolkits/clientary/framework/cursor) - [VS Code](https://composio.dev/toolkits/clientary/framework/vscode) - [OpenCode](https://composio.dev/toolkits/clientary/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/clientary/framework/openclaw) - [Hermes](https://composio.dev/toolkits/clientary/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/clientary/framework/cli) - [Google ADK](https://composio.dev/toolkits/clientary/framework/google-adk) - [LangChain](https://composio.dev/toolkits/clientary/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/clientary/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/clientary/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/clientary/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/clientary/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - 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](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - 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](https://composio.dev/toolkits/hubspot) - 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. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place. - [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently. - [Stripe](https://composio.dev/toolkits/stripe) - Stripe is a global online payments platform offering APIs for managing payments, customers, and subscriptions. Trusted by businesses for secure, efficient, and scalable payment processing worldwide. - [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities. - [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Clientary MCP? 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. ### Can I use Tool Router MCP with Pydantic AI? 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. ### Can I manage the permissions and scopes for Clientary while using Tool Router? 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. ### How safe is my data with Composio Tool Router? 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. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)