Build AI Video Workflows Faster with Pictory MCP Server API

What Is the Pictory MCP Server?

At Pictory, we provide powerful APIs for turning text, scripts, and long-form content into engaging videos. As developers and AI assistants began building richer, more intelligent workflows, we saw an opportunity: To provide a simpler, more unified way to access and compose video creation capabilities.

Enter the Pictory MCP Server — a powerful tool that simplifies and enhances the video editing process for users. This lightweight, MCP-compliant server exposes a set of focused tools like create-storyboard or get-video-template. These tools abstract away API complexity, encapsulating multi-step operations like input validation, retries, and data transformation behind clean, declarative interfaces.

By implementing the Model Context Protocol (MCP), the server integrates seamlessly with AI assistants like Claude, automation frameworks, and other MCP clients — enabling them to discover available capabilities and orchestrate workflows through natural language.

With Pictory MCP Server, both developers and end-users of tools like Claude Desktop and Cursor can harness Pictory’s full video generation pipeline — with no custom code or low-level API knowledge — unlocking new possibilities for automation, personalization, and conversational content creation.

Why We Built It

As developers pushed the boundaries of our video generation APIs—incorporating voiceovers, intricate scene assembly, and advanced rendering—a consistent challenge emerged: Orchestrating these powerful capabilities intelligently was complex and time-consuming. While our APIs handled individual steps, coordinating them into seamless workflows meant wrestling with API mechanics, managing payloads, polling for status, sequencing operations, and handling errors. This ‘API fatigue’ was slowing down innovation.

With AI agents becoming more sophisticated and MCP emerging as a standard for tool integration, we saw a unique opportunity: make Pictory’s video generation pipeline accessible not just to developers writing custom code, but to AI assistants, automated workflows, and end-users — all without requiring deep API knowledge.

Consider a typical workflow: depending on the type of video a user wants to create, the system automatically selects the most suitable template from a library of options, personalizes it with the right variables — such as brand colors, text overlays, or logo — generates a voiceover, and renders the final video. While our APIs support each of these steps, coordinating them still required significant orchestration — managing payloads, polling for status, sequencing operations, and handling errors.

We envisioned something better.

This vision led to the Pictory MCP Server: a modular, MCP-compliant toolset that transforms our video generation pipeline into a collection of high-level, discoverable operations. Instead of managing API mechanics, users simply express their creative intent — and MCP clients like Claude handle the orchestration by chaining together the right tools in real time.

The Pictory MCP Server offers features such as advanced automation, seamless customization, and integration options that distinguish it from traditional solutions.

How It Works

The Pictory MCP Server takes a modular approach, instead of enforcing rigid workflows, it exposes a set of composable tools that MCP clients can use to create intelligent, personalized video pipelines. The MCP Server is made up of individual components, such as infrastructure modules, APIs, security measures, and deployment tools, that work together to enable flexible video workflows.

Tool-Based Architecture and Client-Driven Orchestration

When an MCP client connects to the server, it automatically discovers a set of focused tools via the MCP protocol. Each tool encapsulates a specific capability, such as selecting a template, creating a storyboard, or rendering a final video, with clearly defined inputs and outputs. Each tool is accessible via a specific endpoint within the MCP Server, ensuring that clients can interact with the correct URL path for each capability.

This design empowers MCP clients, like Claude Desktop, to dynamically compose video workflows by chaining these exposed tools. For instance, imagine a user simply asks Claude to ‘create a video.’ Behind the scenes, the client can:

• Call get-all-video-templates to list available options.
• Use get-video-template-detail to inspect candidates.
• Select the most suitable template and run create-storyboard-from-template.
• Finally, invoke render-video to generate the final output.

Each of these steps is executed through the MCP Server, which expertly manages the underlying API calls, data flow, retries, and error handling. This abstraction allows clients to focus entirely on understanding user intent and orchestrating the creative process, while relying on the server for robust execution logic.

Flexibility with Standards

Because each tool adheres to the MCP standard, clients can automatically discover available capabilities and invoke them through structured protocols, no custom integrations needed. The result is a system where complex video creation can be driven by natural input, composed on the fly, and executed with precision, combining client-side intelligence with Pictory’s video expertise behind the scenes.

Using It

Getting started with the Pictory MCP Server is straightforward, simply configure your MCP client to connect to the MCP server.

Configuration for Claude Desktop

1. After installing Claude Desktop, open Settings > Developer

2. Click Edit Config button and it would open the location of file
   claude_desktop_config.json

3. Open this file for editing - if there are no MCP Servers, it would look like this. 

4. Add the following Pictory MCP configurations to this file. You need Pictory API Client ID and Client Secret for this configuration. If you do not have these, please contact us.

{

  "pictory": {

    "command": "npx",

    "args": ["-y", "@pictory/pictory-mcp-server"],

    "env": {

      "PICTORY_API_BASE_URL": "https://api.pictory.ai/pictoryapis/v1",

      "PICTORY_CLIENT_ID": "your_client_id",

      "PICTORY_CLIENT_SECRET": "your_client_secret",

      "PICTORY_USER_ID": "your_user_id"

    }

  }

The final config file would look like this.

5. Restart Claude Desktop and when you click on the “Search and tools” button, you should see the pictory menu option with multiple tools.

Details of MCP on Claude Desktop can be found here. 

Further details of Pictory MCP Server and configuration can be found here.

Natural Language Interaction 

Once configured, you can interact with Pictory through natural conversation in Claude Desktop:

Behind the scenes, Claude automatically chains the appropriate tools — create-storyboard, poll-storyboard-job-status, get-storyboard-preview, render-video, and get-rendered-video-url — to deliver your final video.

Template-Based Workflows You can also leverage Pictory's template library:

Claude will use get-all-video-templates and get-video-template-detail to explore options, then create-storyboard-from-template to generate your customized video.

The true elegance of this approach lies in how complex video creation workflows become as simple as describing what you want in plain English. All the technical orchestration is handled automatically by your MCP client and Pictory MCP Server, freeing you to focus purely on creative output.

What’s Next

The Pictory MCP Server represents just the beginning of our vision for making AI-powered video creation more accessible and composable.

We’re continuing to expand its capabilities — making it easier for developers, AI agents and end-users to create videos that are not only automated, but personalized and production-ready.

On the roadmap:

• Expand the library of available commands — video transcription and summarization, video draft approval and many more
• Support more input types — Powerpoint, PDF, Google Docs
• Cloud-hosted MCP server for seamless deployment without setup
• Agent registry to allow custom extensions and third-party integrations
• Deeper AI assistant integrations with no-code platforms such as Zapier and Make.

Ultimately, our goal is to ensure Pictory's cutting-edge capabilities are accessible wherever creativity happens, whether through a developer tool, a sophisticated chatbot, or a simple voice prompt.

Ready to revolutionize your video workflows? We invite you to explore the Pictory MCP Server, share your valuable feedback, and even contribute to its evolution.

Frequently Asked Questions

How do I get my Pictory Client ID and Secret?

Contact support@pictory.ai to request your credentials

What tools does the MCP Server expose?

Tools include: get-all-video-templates, get-video-template-detail, create-storyboard, poll-storyboard-job-status, render-video.

Can Claude or other LLMs use this server directly?

Yes. Any LLM that supports the Model Context Protocol (MCP), including Claude, can use the tools exposed by the server.

Do I need to write code to use this?

No. Claude and other MCP-compatible LLMs handle orchestration via natural language prompts.