# How to integrate Placid MCP with Pydantic AI

```json
{
  "title": "How to integrate Placid MCP with Pydantic AI",
  "toolkit": "Placid",
  "toolkit_slug": "placid",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/placid/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/placid/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:22:11.363Z"
}
```

## Introduction

This guide walks you through connecting Placid to Pydantic AI using the Composio tool router. By the end, you'll have a working Placid agent that can create a linkedin banner template for me, delete last week's event flyer template, list all pdf template collections in your account through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Placid account through Composio's Placid MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Placid with

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

The Placid MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Placid account. It provides structured and secure access to your creative automation workspace, so your agent can perform actions like creating image templates, managing template collections, and deleting designs on your behalf.
- Template creation and customization: Instantly generate new Placid templates with defined dimensions, tags, or custom metadata—perfect for automating banners, graphics, and more.
- Template deletion and lifecycle management: Direct your agent to safely remove obsolete or unused templates by their unique IDs, keeping your workspace organized and clutter-free.
- Collection retrieval and organization: Have your agent fetch and list all template collections, making it easy to browse, search, or group creative assets programmatically.
- Automated workflow integration: Integrate template management into larger creative pipelines, allowing your agent to handle content operations without manual intervention.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PLACID_CREATE_COLLECTION` | Create Collection | Tool to create a new template collection to group multiple templates. Use when organizing templates into collections with custom metadata. |
| `PLACID_CREATE_TEMPLATE` | Create Template | Tool to create a new Placid template. Use when you need a template with specific dimensions and optional tags or custom metadata. Example: "Create a social-media banner." |
| `PLACID_DELETE_COLLECTION` | Delete Collection | Tool to delete a template collection by its ID. Use after confirming the collection is no longer needed. Note: This does not delete the templates within the collection. |
| `PLACID_DELETE_TEMPLATE` | Delete Template | Tool to delete a specific template identified by UUID. Use after confirming the template is no longer needed. |
| `PLACID_GET_COLLECTION` | Get Collection | Tool to retrieve a single collection by its ID. Use when you need details about a specific collection including its title, custom data, and associated template UUIDs. |
| `PLACID_GET_COLLECTIONS` | Get Collections | Tool to retrieve a list of all template collections. Use after authentication to paginate through your Placid collections. |
| `PLACID_GET_TEMPLATE` | Get Template | Tool to retrieve a template by UUID. Returns template details including title, thumbnail, tags, and layers. |
| `PLACID_LIST_NL_TEMPLATES` | List NL Templates | Tool to list all available templates via the Natural Language API. Use when you need to discover available templates for generating images. |
| `PLACID_LIST_TEMPLATES` | List Templates | Tool to retrieve a list of templates from your project. Returns 20 items per page with cursor pagination. Use to browse templates, optionally filtered by collection or title. |
| `PLACID_UPDATE_COLLECTION` | Update Collection | Tool to update an existing template collection. Use to modify title, custom_data, or manage templates (replace all, or incrementally add/remove specific templates). |
| `PLACID_UPDATE_TEMPLATE` | Update Template | Tool to update an existing Placid template. Use when you need to modify the title, tags, or custom_data of a template. |

## Supported Triggers

None listed.

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

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

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

## Related Toolkits

- [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.
- [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.
- [Alttext ai](https://composio.dev/toolkits/alttext_ai) - AltText.ai is a service that generates alt text for images automatically. It helps boost accessibility and SEO for your visual content.
- [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.
- [Canva](https://composio.dev/toolkits/canva) - Canva is a drag-and-drop design suite for creating professional graphics, presentations, and marketing materials. It makes it easy for anyone to design with beautiful templates and a vast library of elements.
- [Claid ai](https://composio.dev/toolkits/claid_ai) - Claid.ai delivers AI-driven image editing APIs for tasks like background removal, upscaling, and color correction. It helps automate and enhance image workflows with powerful, developer-friendly tools.
- [Cloudinary](https://composio.dev/toolkits/cloudinary) - Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally.
- [Cults](https://composio.dev/toolkits/cults) - Cults is a digital marketplace for 3D printing models, connecting designers and makers. It lets creators share, sell, and discover a huge variety of printable designs easily.
- [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks.
- [Dreamstudio](https://composio.dev/toolkits/dreamstudio) - DreamStudio is Stability AI’s platform for generating and editing images with AI. It lets you easily turn ideas into stunning visuals, fast.
- [Dynapictures](https://composio.dev/toolkits/dynapictures) - Dynapictures is a cloud-based platform for generating personalized images at scale. Instantly create hundreds of custom visuals using your data sources, like Google Sheets.
- [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools.
- [Gamma](https://composio.dev/toolkits/gamma) - Gamma is an AI-powered platform for making beautiful, interactive presentations and documents. It lets anyone create and share engaging decks with minimal effort.
- [Html to image](https://composio.dev/toolkits/html_to_image) - Html to image converts HTML and CSS into images or captures web page screenshots. Instantly generate visuals from code or web content—no manual screenshots needed.
- [Imagior](https://composio.dev/toolkits/imagior) - Imagior is an AI-powered image generation platform that lets you create and customize images using dynamic templates and APIs. Perfect for businesses and creators needing fast, scalable visuals without design hassle.
- [Imejis io](https://composio.dev/toolkits/imejis_io) - Imejis io is an API-based image generation platform with powerful customization and template support. It lets you create and modify images in seconds, no manual design work required.
- [Imgix](https://composio.dev/toolkits/imgix) - Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale.
- [Kraken io](https://composio.dev/toolkits/kraken_io) - Kraken.io is an image optimization and compression platform. It helps you shrink image file sizes while keeping visual quality intact.
- [Logo dev](https://composio.dev/toolkits/logo_dev) - Logo.dev is an API and database for high-resolution company logos and brand metadata. Instantly fetch official logos from any domain without scraping or manual searching.
- [Miro](https://composio.dev/toolkits/miro) - Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space.

## Frequently Asked Questions

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

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

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
