# How to integrate DeepImage MCP with Pydantic AI ```json { "title": "How to integrate DeepImage MCP with Pydantic AI", "toolkit": "DeepImage", "toolkit_slug": "deepimage", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/deepimage/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/deepimage/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:29:57.483Z" } ``` ## Introduction This guide walks you through connecting DeepImage to Pydantic AI using the Composio tool router. By the end, you'll have a working DeepImage agent that can enhance and upscale this low-res image, apply ai noise reduction to a photo, convert given image to hd quality through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a DeepImage account through Composio's DeepImage MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate DeepImage with - [OpenAI Agents SDK](https://composio.dev/toolkits/deepimage/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/deepimage/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/deepimage/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/deepimage/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/deepimage/framework/codex) - [OpenClaw](https://composio.dev/toolkits/deepimage/framework/openclaw) - [Hermes](https://composio.dev/toolkits/deepimage/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/deepimage/framework/cli) - [Google ADK](https://composio.dev/toolkits/deepimage/framework/google-adk) - [LangChain](https://composio.dev/toolkits/deepimage/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/deepimage/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/deepimage/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/deepimage/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/deepimage/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 DeepImage - 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 DeepImage 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 DeepImage MCP server, and what's possible with it? The DeepImage MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your DeepImage account. It provides structured and secure access so your agent can perform DeepImage operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `DEEPIMAGE_DELETE_JOB` | Delete Job | Tool to delete completed job result and remove images from the server. Use when cleaning up processed jobs that are no longer needed. | | `DEEPIMAGE_GET_ACCOUNT_INFO` | Get Account Information | Tool to retrieve authenticated user's profile information including credits, username, email, API key, language preference, webhook settings, and billing address. Use when you need to check account details or credit balance. | | `DEEPIMAGE_GET_JOB_RESULT` | Get Job Result | Tool to retrieve processing job result by hash. Use to check job status and get result URL when processing is complete. | | `DEEPIMAGE_PROCESS_IMAGE_ASYNC` | Process Image Async | Tool to schedule an image enhancement job and wait for the result. Performs selected enhancement options on an image and returns the result URL if processing completes within 25 seconds; otherwise returns a job hash for later retrieval. Use when you need to enhance images with options like denoising, deblurring, lighting improvements, or background removal. | | `DEEPIMAGE_PROCESS_IMAGE_SYNCHRONOUSLY` | Process Image Synchronously | Tool to process an image synchronously with Deep Image AI. Returns result URL immediately if processing completes in less than 25 seconds, otherwise returns job hash for async polling. Use for image enhancement, resizing, background removal, and other image processing tasks. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The DeepImage MCP server is an implementation of the Model Context Protocol that connects your AI agent to DeepImage. It provides structured and secure access so your agent can perform DeepImage 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 DeepImage - 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 DeepImage - MCPServerStreamableHTTP connects to the DeepImage 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 DeepImage 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 DeepImage composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["deepimage"], ) 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 DeepImage endpoint - The agent uses GPT-5 to interpret user commands and perform DeepImage operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent deepimage_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[deepimage_mcp], instructions=( "You are a DeepImage assistant. Use DeepImage 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 - DeepImage 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 DeepImage.\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 DeepImage composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["deepimage"], ) 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 deepimage_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[deepimage_mcp], instructions=( "You are a DeepImage assistant. Use DeepImage 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 DeepImage.\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 DeepImage through Composio's Tool Router. With this setup, your agent can perform real DeepImage 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 + DeepImage 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 DeepImage MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/deepimage/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/deepimage/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/deepimage/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/deepimage/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/deepimage/framework/codex) - [OpenClaw](https://composio.dev/toolkits/deepimage/framework/openclaw) - [Hermes](https://composio.dev/toolkits/deepimage/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/deepimage/framework/cli) - [Google ADK](https://composio.dev/toolkits/deepimage/framework/google-adk) - [LangChain](https://composio.dev/toolkits/deepimage/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/deepimage/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/deepimage/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/deepimage/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/deepimage/framework/crew-ai) ## Related Toolkits - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service. - [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows. - [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. - [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow. - [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. - [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows. - [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application. - [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities. - [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. - [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization. - [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications. - [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations. - [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key. - [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. - [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient. - [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions. - [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences. - [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. - [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and DeepImage MCP? With a standalone DeepImage MCP server, the agents and LLMs can only access a fixed set of DeepImage tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from DeepImage 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 DeepImage tools. ### Can I manage the permissions and scopes for DeepImage while using Tool Router? Yes, absolutely. You can configure which DeepImage 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 DeepImage data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)