# How to integrate Shotstack MCP with Pydantic AI ```json { "title": "How to integrate Shotstack MCP with Pydantic AI", "toolkit": "Shotstack", "toolkit_slug": "shotstack", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/shotstack/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/shotstack/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:26:06.027Z" } ``` ## Introduction This guide walks you through connecting Shotstack to Pydantic AI using the Composio tool router. By the end, you'll have a working Shotstack agent that can create a video slideshow from uploaded images, generate a branded video intro with logo, combine multiple video clips into one file through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Shotstack account through Composio's Shotstack MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Shotstack with - [OpenAI Agents SDK](https://composio.dev/toolkits/shotstack/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/shotstack/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/shotstack/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/shotstack/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/shotstack/framework/codex) - [OpenClaw](https://composio.dev/toolkits/shotstack/framework/openclaw) - [Hermes](https://composio.dev/toolkits/shotstack/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/shotstack/framework/cli) - [Google ADK](https://composio.dev/toolkits/shotstack/framework/google-adk) - [LangChain](https://composio.dev/toolkits/shotstack/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/shotstack/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/shotstack/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/shotstack/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/shotstack/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 Shotstack - 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 Shotstack 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 Shotstack MCP server, and what's possible with it? The Shotstack MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Shotstack account. It provides structured and secure access to powerful video, image, and audio automation features—so your agent can create dynamic media content, edit assets, manage rendering jobs, and retrieve results at scale on your behalf. - Automated video and image generation: Let your agent assemble and render videos or images programmatically using templates, custom assets, and dynamic data. - Media editing and composition: Enable your agent to cut, trim, overlay, and combine media clips—adding text, transitions, or audio tracks as needed. - Batch rendering and job management: Have your agent submit, track, and manage multiple rendering jobs, so you can scale creative automation for campaigns or client deliverables. - Asset and template organization: Allow your agent to upload, list, and organize reusable templates and media assets, keeping your creative workflow streamlined. - Result retrieval and download: Automatically fetch completed renders and download media files, making finished content instantly available for distribution or review. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SHOTSTACK_CREATE_TEMPLATE` | Create Template | Tool to create a new template for video editing. Use when you want to save a reusable timeline configuration as a template. Template changes do not retroactively affect past renders. | | `SHOTSTACK_CREATE_TEMPLATE2` | Create Template (v2) | Tool to save an Edit as a re-usable template. Templates can be retrieved and modified before rendering. Use when you want to create a template with merge fields for dynamic content. | | `SHOTSTACK_DELETE_INGESTED_MEDIA` | Delete Ingested Media | Tool to delete an ingested media asset. Use when you've confirmed the ingest ID and need to remove the file from Shotstack storage. | | `SHOTSTACK_DELETE_TEMPLATE2` | Delete Template | Tool to delete a specific Shotstack template by its ID. Use when you need to remove a template permanently. | | `SHOTSTACK_DELETE_WORKFLOW` | Delete Shotstack Workflow | Tool to delete a specific Shotstack workflow. Use when you need to permanently remove a workflow after confirming its ID. | | `SHOTSTACK_FETCH_SOURCE` | Fetch Source | Tool to fetch a remote media file and store it as a source asset. Operation is asynchronous — poll SHOTSTACK_GET_INGEST_STATUS or SHOTSTACK_INSPECT_MEDIA until the asset is ready before passing it to SHOTSTACK_RENDER_VIDEO or other downstream tools. Use when you need to ingest a file before rendering. | | `SHOTSTACK_GET_ASSETS` | Get Asset | Tool to fetch details of a hosted asset by its unique identifier. Use when you need to retrieve information about videos, images, audio files, thumbnails, or poster images hosted on Shotstack's CDN. | | `SHOTSTACK_GET_ASSETS_RENDER` | Get Assets by Render ID | Tool to retrieve hosted assets by render ID. Use when you need to fetch one or more files (video, thumbnail, poster image) generated by a specific render job. | | `SHOTSTACK_GET_RENDER_CALLBACK` | Get Render Callback | Tool to retrieve the webhook/callback URL configuration for a specific render job. Returns only callback settings (URL, method, headers), not render status or output URLs — use a separate render-status check to obtain final results. | | `SHOTSTACK_GET_RENDER_STATUS` | Get Render Status | Tool to retrieve the current status and details of a Shotstack render job by render ID. Use when polling a render until done or failed, typically after creating a render with SHOTSTACK_RENDER_VIDEO. | | `SHOTSTACK_GET_SOURCE` | Get Source Details | Tool to fetch the details of a specific source asset. Use when you need to inspect a source after uploading, check its status, or diagnose ingest/render failures—such as unsupported codecs, corrupt files, or bad URLs—before retrying. | | `SHOTSTACK_GET_TEMPLATE` | Get Template | Tool to retrieve details of a specific template. Use when you have the ID of an existing template and need its metadata. | | `SHOTSTACK_GET_TEMPLATE_BY_VERSION` | Get Template By Version | Tool to retrieve a template by template id and API version. Use when you need to fetch template details from a specific Edit API version. | | `SHOTSTACK_GET_UPLOAD_URL` | Get Upload URL | Tool to request a signed URL for direct file upload to Shotstack. Use when you need to upload a file to Shotstack storage. The response returns a signed URL that you use to upload the file using a PUT request with the binary file. | | `SHOTSTACK_INSPECT_MEDIA` | Inspect Media | Tool to inspect media metadata. Use before rendering to retrieve duration, resolution, frame rate, and format of an online media file — clip timecodes, trim points, and audio sync calculations depend on these values. Mixing assets without prior inspection can cause letterboxing, jitter, or audio sync issues in the final output. | | `SHOTSTACK_LIST_SOURCES` | List Sources | Tool to list all source assets. Use when you need to retrieve source entries with optional pagination. | | `SHOTSTACK_LIST_SOURCES2` | List Sources (with Environment) | Tool to list all ingested source files with environment selection. Use when you need to retrieve sources from stage (sandbox) or v1 (production) environment with optional pagination. | | `SHOTSTACK_LIST_TEMPLATES` | List Templates | Tool to list all Shotstack templates for the account. Use after creating or updating templates to view your available templates. | | `SHOTSTACK_LIST_TEMPLATES2` | List Templates with Environment | Tool to list all Shotstack templates for the specified environment. Use when you need to retrieve templates from a specific environment (stage or production). | | `SHOTSTACK_POST_UPLOAD` | Request Upload URL | Tool to request a signed URL for direct file upload. Use when you need to upload a file to Shotstack storage. The response returns a signed URL that expires in one hour. | | `SHOTSTACK_RENDER_VIDEO` | Render Video | Tool to initiate a new video render job. Use when you have defined a timeline and output settings and want to start rendering. | | `SHOTSTACK_TRANSFER_ASSET` | Transfer Asset | Tool to transfer a file from any publicly available URL to one or more Serve API destinations. Use when you need to copy a file from an external source to Shotstack's hosting service or other configured destinations. | | `SHOTSTACK_UPDATE_TEMPLATE` | Update Template | Tool to update an existing template by its ID. Use when you need to modify a template's name or edit configuration. Both name and complete template definition must be provided. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Shotstack MCP server is an implementation of the Model Context Protocol that connects your AI agent to Shotstack. It provides structured and secure access so your agent can perform Shotstack 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 Shotstack - 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 Shotstack - MCPServerStreamableHTTP connects to the Shotstack 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 Shotstack 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 Shotstack composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["shotstack"], ) 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 Shotstack endpoint - The agent uses GPT-5 to interpret user commands and perform Shotstack operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent shotstack_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[shotstack_mcp], instructions=( "You are a Shotstack assistant. Use Shotstack 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 - Shotstack 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 Shotstack.\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 Shotstack composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["shotstack"], ) 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 shotstack_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[shotstack_mcp], instructions=( "You are a Shotstack assistant. Use Shotstack 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 Shotstack.\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 Shotstack through Composio's Tool Router. With this setup, your agent can perform real Shotstack 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 + Shotstack 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 Shotstack MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/shotstack/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/shotstack/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/shotstack/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/shotstack/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/shotstack/framework/codex) - [OpenClaw](https://composio.dev/toolkits/shotstack/framework/openclaw) - [Hermes](https://composio.dev/toolkits/shotstack/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/shotstack/framework/cli) - [Google ADK](https://composio.dev/toolkits/shotstack/framework/google-adk) - [LangChain](https://composio.dev/toolkits/shotstack/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/shotstack/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/shotstack/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/shotstack/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/shotstack/framework/crew-ai) ## Related Toolkits - [Youtube](https://composio.dev/toolkits/youtube) - YouTube is a leading video-sharing platform for uploading, streaming, and discovering content. It empowers creators and businesses to reach global audiences and monetize their work. - [Amara](https://composio.dev/toolkits/amara) - Amara is a collaborative platform for creating and managing subtitles and captions for videos. It helps make content accessible and multilingual for global audiences. - [Cats](https://composio.dev/toolkits/cats) - Cats is an API with a huge library of cat images, breed data, and cat facts. It makes finding adorable cat photos and trivia effortless for your apps and users. - [Chatfai](https://composio.dev/toolkits/chatfai) - Chatfai is an AI platform that lets users talk to AI versions of fictional characters from books, movies, and games. It offers an engaging, interactive experience for fans to chat, roleplay, and explore creative dialogues. - [Cincopa](https://composio.dev/toolkits/cincopa) - Cincopa is a multimedia platform for uploading, managing, and customizing videos, images, and audio. It helps you deliver engaging media experiences with robust APIs and flexible integrations. - [Dungeon fighter online](https://composio.dev/toolkits/dungeon_fighter_online) - Dungeon Fighter Online (DFO) is an arcade-style, side-scrolling action RPG packed with dynamic combat and progression. Play solo or with friends to battle monsters, complete quests, and upgrade your characters. - [Elevenlabs](https://composio.dev/toolkits/elevenlabs) - Elevenlabs is an advanced AI voice generation platform for lifelike, multilingual speech synthesis. Perfect for creating natural voices for videos, apps, and business content in seconds. - [Elevenreader](https://composio.dev/toolkits/elevenreader) - Elevenreader is an AI-powered text-to-speech service by ElevenLabs that converts written content into lifelike audio. It enables fast, natural audio generation from any text. - [Epic games](https://composio.dev/toolkits/epic_games) - Epic Games is a leading video game publisher and digital storefront, known for Fortnite and Unreal Engine. It lets gamers access, manage, and purchase games all in one place. - [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. - [Giphy](https://composio.dev/toolkits/giphy) - Giphy is the largest online library for searching and sharing GIFs and stickers. Instantly add vibrant animated content to your apps, chats, and workflows. - [Headout](https://composio.dev/toolkits/headout) - Headout is a global platform for booking travel experiences, tours, and entertainment. It helps users discover and secure activities at top destinations, all in one place. - [Imagekit io](https://composio.dev/toolkits/imagekit_io) - ImageKit.io is a cloud-based media management platform for image and video delivery. Instantly optimize, transform, and deliver visuals globally via a lightning-fast CDN. - [Listennotes](https://composio.dev/toolkits/listennotes) - Listennotes is a powerful podcast search engine with a massive global database. Discover, search, and curate podcasts from around the world in seconds. - [News api](https://composio.dev/toolkits/news_api) - News api is a REST API for searching and retrieving live news articles from across the web. Instantly access headlines, coverage, and breaking stories from thousands of sources. - [RAWG Video Games Database](https://composio.dev/toolkits/rawg_video_games_database) - RAWG Video Games Database is the largest video game discovery and info service. Instantly access comprehensive details, ratings, and release dates for thousands of games. - [Seat geek](https://composio.dev/toolkits/seat_geek) - SeatGeek is a live event platform offering APIs for concerts, sports, and theater data. Instantly access events, venues, and performers info for smarter ticketing and discovery. - [Spotify](https://composio.dev/toolkits/spotify) - Spotify is a streaming service for music and podcasts with millions of tracks from artists worldwide. Enjoy personalized playlists, recommendations, and seamless listening across all your devices. - [Ticketmaster](https://composio.dev/toolkits/ticketmaster) - Ticketmaster is a global platform for event discovery, ticket sales, and live entertainment management. Get real-time access to events and streamline ticketing for fans and organizers. - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Shotstack MCP? With a standalone Shotstack MCP server, the agents and LLMs can only access a fixed set of Shotstack tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Shotstack 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 Shotstack tools. ### Can I manage the permissions and scopes for Shotstack while using Tool Router? Yes, absolutely. You can configure which Shotstack 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 Shotstack data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)