# How to integrate Supportivekoala MCP with Pydantic AI ```json { "title": "How to integrate Supportivekoala MCP with Pydantic AI", "toolkit": "Supportivekoala", "toolkit_slug": "supportivekoala", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/supportivekoala/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/supportivekoala/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:27:35.620Z" } ``` ## Introduction This guide walks you through connecting Supportivekoala to Pydantic AI using the Composio tool router. By the end, you'll have a working Supportivekoala agent that can create a personalized welcome image for new users, generate event flyers using your saved template, list all image templates i’ve set up through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Supportivekoala account through Composio's Supportivekoala MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Supportivekoala with - [OpenAI Agents SDK](https://composio.dev/toolkits/supportivekoala/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/supportivekoala/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/supportivekoala/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/supportivekoala/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/supportivekoala/framework/codex) - [OpenClaw](https://composio.dev/toolkits/supportivekoala/framework/openclaw) - [Hermes](https://composio.dev/toolkits/supportivekoala/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/supportivekoala/framework/cli) - [Google ADK](https://composio.dev/toolkits/supportivekoala/framework/google-adk) - [LangChain](https://composio.dev/toolkits/supportivekoala/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/supportivekoala/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/supportivekoala/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/supportivekoala/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/supportivekoala/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 Supportivekoala - 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 Supportivekoala 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 Supportivekoala MCP server, and what's possible with it? The Supportivekoala MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Supportivekoala account. It provides structured and secure access to your image generation workflows, so your agent can create images, manage templates, retrieve image lists, and automate visual content creation entirely on your behalf. - Automated image creation using templates: Instantly generate custom images by selecting and modifying templates with dynamic data, all through your agent. - Template management and customization: Let your agent create new templates for recurring graphic needs or update existing ones to fit fresh branding and messaging. - Image and asset retrieval: Effortlessly list all images generated by your account, allowing your agent to fetch, manage, or reference previous visual assets as needed. - Template discovery and details: Retrieve and review all available templates, or fetch full details for any template using its ID—perfect for scaling up campaigns or personalizing content. - User registration automation: Seamlessly create new user accounts so your workflows can onboard new teammates or clients without manual intervention. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SUPPORTIVEKOALA_CREATE_IMAGE` | Create Image | Tool to create a new image based on a template. Use when you have selected your template and prepared modifications. | | `SUPPORTIVEKOALA_CREATE_TEMPLATE` | Create Template | Tool to create a new template for image generation. Use after gathering template details. | | `SUPPORTIVEKOALA_LIST_IMAGES` | List Images | Tool to list images associated with the authenticated user. Use after confirming authentication. | | `SUPPORTIVEKOALA_LIST_TEMPLATES` | List Templates | Tool to retrieve all templates. Use when you need to list all templates for the authenticated user. | | `SUPPORTIVEKOALA_REGISTER_USER` | Register User | Tool to register a new user account. Use after collecting valid user credentials. | | `SUPPORTIVEKOALA_RETRIEVE_TEMPLATE` | Retrieve Template by ID | Tool to retrieve a template by ID. Use when you have a valid template ID and need full template details. Use after confirming this detail. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Supportivekoala MCP server is an implementation of the Model Context Protocol that connects your AI agent to Supportivekoala. It provides structured and secure access so your agent can perform Supportivekoala 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 Supportivekoala - 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 Supportivekoala - MCPServerStreamableHTTP connects to the Supportivekoala 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 Supportivekoala 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 Supportivekoala composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["supportivekoala"], ) 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 Supportivekoala endpoint - The agent uses GPT-5 to interpret user commands and perform Supportivekoala operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent supportivekoala_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[supportivekoala_mcp], instructions=( "You are a Supportivekoala assistant. Use Supportivekoala 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 - Supportivekoala 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 Supportivekoala.\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 Supportivekoala composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["supportivekoala"], ) 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 supportivekoala_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[supportivekoala_mcp], instructions=( "You are a Supportivekoala assistant. Use Supportivekoala 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 Supportivekoala.\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 Supportivekoala through Composio's Tool Router. With this setup, your agent can perform real Supportivekoala 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 + Supportivekoala 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 Supportivekoala MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/supportivekoala/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/supportivekoala/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/supportivekoala/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/supportivekoala/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/supportivekoala/framework/codex) - [OpenClaw](https://composio.dev/toolkits/supportivekoala/framework/openclaw) - [Hermes](https://composio.dev/toolkits/supportivekoala/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/supportivekoala/framework/cli) - [Google ADK](https://composio.dev/toolkits/supportivekoala/framework/google-adk) - [LangChain](https://composio.dev/toolkits/supportivekoala/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/supportivekoala/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/supportivekoala/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/supportivekoala/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/supportivekoala/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Supportivekoala MCP? With a standalone Supportivekoala MCP server, the agents and LLMs can only access a fixed set of Supportivekoala tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Supportivekoala 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 Supportivekoala tools. ### Can I manage the permissions and scopes for Supportivekoala while using Tool Router? Yes, absolutely. You can configure which Supportivekoala 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 Supportivekoala data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)