# How to integrate TinyPNG MCP with CrewAI ```json { "title": "How to integrate TinyPNG MCP with CrewAI", "toolkit": "TinyPNG", "toolkit_slug": "tinypng", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/tinypng/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/tinypng/framework/crew-ai.md", "updated_at": "2026-05-12T10:28:40.911Z" } ``` ## Introduction This guide walks you through connecting TinyPNG to CrewAI 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 CrewAI 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) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your TinyPNG connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for TinyPNG - Build a conversational loop where your agent can execute TinyPNG operations ## What is CrewAI? CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews. Key features include: - Agent Roles: Define specialized agents with specific goals and backstories - Task Management: Create tasks with clear descriptions and expected outputs - Crew Orchestration: Combine agents and tasks into collaborative workflows - MCP Integration: Connect to external tools through Model Context Protocol ## 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 and API key - A TinyPNG connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 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 **What's happening:** - composio connects your agent to TinyPNG via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates with Composio - USER_ID scopes the session to your account - OPENAI_API_KEY lets CrewAI use your chosen OpenAI model ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **What's happening:** - CrewAI classes define agents and tasks, and run the workflow - MCPServerHTTP connects the agent to an MCP endpoint - Composio will give you a short lived TinyPNG MCP URL ```python import os from composio import Composio from crewai import Agent, Task, Crew from crewai_tools import MCPServerAdapter import dotenv dotenv.load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") ``` ### 5. Create a Composio Tool Router session for TinyPNG **What's happening:** - You create a TinyPNG only session through Composio - Composio returns an MCP HTTP URL that exposes TinyPNG tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["tinypng"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **What's Happening:** - Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication. - MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format. - Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools. - Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops. - Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries. ```python server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users search the internet effectively", backstory="You are a helpful assistant with access to search tools.", tools=tools, verbose=False, max_iter=10, ) ``` ### 7. Create a CLI Chatloop and define the Crew **What's Happening:** - Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable. - Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean. - Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses. - Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context. - Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response. - Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity. ```python print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Complete Code ```python from crewai import Agent, Task, Crew, LLM from crewai_tools import MCPServerAdapter from composio import Composio from dotenv import load_dotenv import os load_dotenv() GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not GOOGLE_API_KEY: raise ValueError("GOOGLE_API_KEY is not set in the environment.") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment.") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment.") # Initialize Composio and create a session composio = Composio(api_key=COMPOSIO_API_KEY) session = composio.create( user_id=COMPOSIO_USER_ID, toolkits=["tinypng"], ) url = session.mcp.url # Configure LLM llm = LLM( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY"), ) server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users with internet searches", backstory="You are an expert assistant with access to Composio Search tools.", tools=tools, llm=llm, verbose=False, max_iter=10, ) print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Conclusion You now have a CrewAI agent connected to TinyPNG through Composio's Tool Router. The agent can perform TinyPNG operations through natural language commands. Next steps: - Add role-specific instructions to customize agent behavior - Plug in more toolkits for multi-app workflows - Chain tasks for complex multi-step operations ## 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) ## 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. 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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 CrewAI? Yes, you can. CrewAI 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)