# How to integrate Pilvio MCP with Pydantic AI

```json
{
  "title": "How to integrate Pilvio MCP with Pydantic AI",
  "toolkit": "Pilvio",
  "toolkit_slug": "pilvio",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/pilvio/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/pilvio/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:22:00.265Z"
}
```

## Introduction

This guide walks you through connecting Pilvio to Pydantic AI using the Composio tool router. By the end, you'll have a working Pilvio agent that can start a new virtual machine with ubuntu, list all active virtual machines in your account, resize an existing vm to a larger instance through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Pilvio account through Composio's Pilvio MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Pilvio with

- [OpenAI Agents SDK](https://composio.dev/toolkits/pilvio/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/pilvio/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/pilvio/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/pilvio/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/pilvio/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/pilvio/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/pilvio/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/pilvio/framework/cli)
- [Google ADK](https://composio.dev/toolkits/pilvio/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/pilvio/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/pilvio/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/pilvio/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/pilvio/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/pilvio/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 Pilvio
- 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 Pilvio 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 Pilvio MCP server, and what's possible with it?

The Pilvio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Pilvio account. It provides structured and secure access to your cloud resources, so your agent can perform actions like provisioning virtual machines, managing object storage, automating infrastructure, and monitoring your resources on your behalf.
- Dynamic virtual machine management: Instantly create, start, stop, or delete virtual machines so your cloud infrastructure adapts to your needs on demand.
- Automated object storage operations: Let your agent upload, download, list, or delete files and buckets for seamless data management in your object storage.
- Infrastructure status monitoring: Query resource states and usage metrics so your agent keeps you informed about cloud health and performance.
- Resource provisioning and automation: Enable your agent to quickly provision new resources, allocate storage, or adjust configurations—without manual intervention.
- Security and access control: Manage API keys, permissions, and access policies to keep your cloud environment secure and compliant.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PILVIO_CHECK_ACTIVE_CAMPAIGNS` | Check Active Campaigns | Tool to check for active campaigns. Use when you need to verify whether any campaigns are currently active. |
| `PILVIO_GET_USER_INFO` | Get User Info | Tool to retrieve information about the authenticated user. Use when you need to fetch the current user's profile after authentication. |
| `PILVIO_LIST_BILLING_ACCOUNTS` | List billing accounts | Tool to list billing accounts. Use when you need to fetch all billing accounts for management or reporting. Use after authenticating your Pilvio API key. |
| `PILVIO_LIST_CREDIT_CARDS` | List Credit Cards | Tool to list credit cards attached to a billing account. Use after confirming the billing account ID. Example: "Retrieve cards for billing_account_id 'ba_1234567890abcdef'." |
| `PILVIO_LIST_INVOICES` | List Invoices | Tool to retrieve a list of invoices. Use after authentication to fetch and filter invoices for a billing account. |
| `PILVIO_LIST_LOCATIONS` | List Pilvio data center locations | Tool to retrieve the list of available data center locations. Use after authentication to see where you can deploy resources. |
| `PILVIO_LIST_VM_RESOURCE_POOLS` | List VM Resource Pools | Tool to retrieve the list of available VM resource pools. Use after authentication to determine where you can provision VMs. |
| `PILVIO_LIST_VMS` | List Virtual Machines | Tool to retrieve a list of all virtual machines. Use after authenticating to fetch your VMs. |
| `PILVIO_LIST_VM_SNAPSHOTS` | List VM Snapshots | Tool to list snapshots (replicas) of a specific VM. Use this to get all point-in-time snapshots or backups for a virtual machine. |
| `PILVIO_UPDATE_USER_PROFILE` | Update User Profile | Tool to update the authenticated user's profile. Use after obtaining a valid API key when you need to modify profile details (e.g., change email or name). |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Pilvio MCP server is an implementation of the Model Context Protocol that connects your AI agent to Pilvio. It provides structured and secure access so your agent can perform Pilvio 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 Pilvio
- 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 Pilvio
- MCPServerStreamableHTTP connects to the Pilvio 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 Pilvio 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 Pilvio
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["pilvio"],
    )
    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 Pilvio endpoint
- The agent uses GPT-5 to interpret user commands and perform Pilvio operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
pilvio_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[pilvio_mcp],
    instructions=(
        "You are a Pilvio assistant. Use Pilvio 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
- Pilvio 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 Pilvio.\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 Pilvio
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["pilvio"],
    )
    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
    pilvio_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[pilvio_mcp],
        instructions=(
            "You are a Pilvio assistant. Use Pilvio 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 Pilvio.\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 Pilvio through Composio's Tool Router. With this setup, your agent can perform real Pilvio 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 + Pilvio 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 Pilvio MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/pilvio/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/pilvio/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/pilvio/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/pilvio/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/pilvio/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/pilvio/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/pilvio/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/pilvio/framework/cli)
- [Google ADK](https://composio.dev/toolkits/pilvio/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/pilvio/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/pilvio/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/pilvio/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/pilvio/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/pilvio/framework/crew-ai)

## Related Toolkits

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- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Pilvio MCP?

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

### Can I manage the permissions and scopes for Pilvio while using Tool Router?

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

---
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