# How to integrate TinyPNG MCP with Pydantic AI ```json { "title": "How to integrate TinyPNG MCP with Pydantic AI", "toolkit": "TinyPNG", "toolkit_slug": "tinypng", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/tinypng/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/tinypng/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:28:40.911Z" } ``` ## Introduction This guide walks you through connecting TinyPNG to Pydantic AI using the Composio tool router. By the end, you'll have a working TinyPNG agent that can compress uploaded png and return link, optimize this jpeg and report savings, convert this image to webp format through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a TinyPNG account through Composio's TinyPNG MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate TinyPNG with - [OpenAI Agents SDK](https://composio.dev/toolkits/tinypng/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/tinypng/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/tinypng/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/tinypng/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/tinypng/framework/codex) - [OpenClaw](https://composio.dev/toolkits/tinypng/framework/openclaw) - [Hermes](https://composio.dev/toolkits/tinypng/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/tinypng/framework/cli) - [Google ADK](https://composio.dev/toolkits/tinypng/framework/google-adk) - [LangChain](https://composio.dev/toolkits/tinypng/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/tinypng/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/tinypng/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/tinypng/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/tinypng/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 TinyPNG - 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 TinyPNG 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 TinyPNG MCP server, and what's possible with it? The TinyPNG MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your TinyPNG account. It provides structured and secure access so your agent can perform TinyPNG operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `TINYPNG_GET_COMPRESSION_COUNT` | Get TinyPNG Compression Count | Tool to retrieve the number of compressions made this month. Use when you need to monitor your TinyPNG API usage. | | `TINYPNG_SHRINK_AND_GET_IMAGE_ID` | Shrink and get image ID | Tool to shrink an image and return its TinyPNG image ID. Use when you need only the compressed image identifier from the API response Location header. | | `TINYPNG_TINIFY_COMPRESS_AND_STORE_IN_AZURE` | Compress and Store Image in Azure | Compress an image using the Tinify API and upload the optimized result directly to Azure Blob Storage in a single operation. The image is first compressed by Tinify, then uploaded to the specified Azure Blob URL using the provided SAS token. Use this when you need to optimize images and store them in Azure without intermediate steps. Supports JPEG, PNG, and WebP image formats. | | `TINYPNG_TINIFY_OUTPUT` | Download Compressed Image | Tool to retrieve a compressed image by its image ID. Use after compressing an image to download the result. | | `TINYPNG_TRANSFORM_IMAGE` | Transform Compressed Image | Tool to transform a compressed image by resizing, converting format, preserving metadata, or storing to cloud storage. Use when you have an image ID from a previous compression and need to apply transformations. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The TinyPNG MCP server is an implementation of the Model Context Protocol that connects your AI agent to TinyPNG. It provides structured and secure access so your agent can perform TinyPNG 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 TinyPNG - 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 TinyPNG - MCPServerStreamableHTTP connects to the TinyPNG 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 TinyPNG 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 TinyPNG composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["tinypng"], ) 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 TinyPNG endpoint - The agent uses GPT-5 to interpret user commands and perform TinyPNG operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent tinypng_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[tinypng_mcp], instructions=( "You are a TinyPNG assistant. Use TinyPNG 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 - TinyPNG 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 TinyPNG.\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 TinyPNG composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["tinypng"], ) 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 tinypng_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[tinypng_mcp], instructions=( "You are a TinyPNG assistant. Use TinyPNG 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 TinyPNG.\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 TinyPNG through Composio's Tool Router. With this setup, your agent can perform real TinyPNG 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 + TinyPNG 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 TinyPNG MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/tinypng/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/tinypng/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/tinypng/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/tinypng/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/tinypng/framework/codex) - [OpenClaw](https://composio.dev/toolkits/tinypng/framework/openclaw) - [Hermes](https://composio.dev/toolkits/tinypng/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/tinypng/framework/cli) - [Google ADK](https://composio.dev/toolkits/tinypng/framework/google-adk) - [LangChain](https://composio.dev/toolkits/tinypng/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/tinypng/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/tinypng/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/tinypng/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/tinypng/framework/crew-ai) ## Related Toolkits - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [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. - [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [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. - [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. 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It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease. - [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training. - [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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and TinyPNG MCP? With a standalone TinyPNG MCP server, the agents and LLMs can only access a fixed set of TinyPNG tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from TinyPNG 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 TinyPNG tools. ### Can I manage the permissions and scopes for TinyPNG while using Tool Router? Yes, absolutely. You can configure which TinyPNG 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 TinyPNG data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)