# How to integrate Abyssale MCP with Pydantic AI

```json
{
  "title": "How to integrate Abyssale MCP with Pydantic AI",
  "toolkit": "Abyssale",
  "toolkit_slug": "abyssale",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/abyssale/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/abyssale/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T09:59:57.453Z"
}
```

## Introduction

This guide walks you through connecting Abyssale to Pydantic AI using the Composio tool router. By the end, you'll have a working Abyssale agent that can create a new project for summer campaign, list all available fonts for a design, get all templates for social media posts through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Abyssale account through Composio's Abyssale MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Abyssale with

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

The Abyssale MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Abyssale account. It provides structured and secure access to your creative automation workspace, so your agent can perform actions like generating projects, retrieving design templates, exploring available fonts, and testing authentication on your behalf.
- Automated project creation and management: Instantly instruct your agent to create new projects for organizing your visual assets and templates, streamlining your creative workflow.
- Template and design discovery: Let your agent fetch and list all available designs, making it easy to browse, filter, and select templates before generating new content.
- Comprehensive font listing: Ask your agent to retrieve all available fonts—including custom and Google fonts—so you can quickly explore typography options for your projects.
- Seamless authentication testing: Have your agent verify your Abyssale API credentials in advance, ensuring every action runs smoothly and securely.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ABYSSALE_AUTHENTICATION_TEST` | Test Abyssale Authentication | Tool to test API authentication via the /ready endpoint. Use after configuring your API key to ensure credentials are valid before other requests. |
| `ABYSSALE_CREATE_PROJECT` | Create Abyssale Project | Tool to create a new project to organize designs and images. Use after deciding on a project name to group your templates and assets. |
| `ABYSSALE_GET_DESIGNS` | Get Designs | Tool to retrieve all designs with optional filtering by category or type. Use after authenticating to list available templates. |
| `ABYSSALE_GET_FONTS` | Get Fonts | Tool to list all available fonts, including custom and Google fonts. Use when you need to fetch font options before generating or editing designs. |

## Supported Triggers

None listed.

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

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

- [OpenAI Agents SDK](https://composio.dev/toolkits/abyssale/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/abyssale/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/abyssale/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/abyssale/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/abyssale/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/abyssale/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/abyssale/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/abyssale/framework/cli)
- [Google ADK](https://composio.dev/toolkits/abyssale/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/abyssale/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/abyssale/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/abyssale/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/abyssale/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/abyssale/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.
- [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.
- [Mural](https://composio.dev/toolkits/mural) - Mural is a digital whiteboard platform for distributed visual collaboration. It helps teams brainstorm, map ideas, and diagram together in real time.

## Frequently Asked Questions

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

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

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

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

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