Runway ML MCP. Generate video assets directly from your chat.
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…and any MCP-compatible client
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Runway ML MCP Server gives your AI agent access to advanced video tools. Generate cinematic clips from text using `text_to_video`, animate still images with `image_to_video`, or blend footage between two key frames using `interpolate`.
It also lets you manage costs and check job status with tools like `get_task` and `cancel_task`. Stop leaving video production to separate web portals.
What your AI agents can do
Cancel task
Stops a video render job immediately, saving your account credits. This action is irreversible.
Gen3 turbo
Generates quick 5-second videos using the Gen-3 Alpha Turbo model based on prompts.
Gen4 turbo
Creates high-quality video footage using the advanced Gen-4 Turbo model.
You run the text_to_video tool and receive a task ID for synthesizing an entirely new, imaginative video scene.
You call either gen3_turbo or gen4_turbo to quickly generate high-quality, model-specific video sequences.
You use image_to_video, specifying a source URL and duration, which animates the static picture into a dynamic clip.
The image_text_to_video tool takes both a reference image and a text prompt to guide exactly how the camera or subject should move.
You run interpolate, which creates smooth, continuous motion footage between two distinct keyframe images.
You use tools like list_tasks or get_task to check if a render succeeded and retrieve the final output URL.
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Supported MCP Clients
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Runway ML MCP Server: 10 Tools for Video Ops
These tools let your AI agent perform every step of the video lifecycle: generating clips from scratch, animating stills, blending footage, and managing costs.
019d7601cancel task
Stops a video render job immediately, saving your account credits. This action is irreversible.
019d7601gen3 turbo
Generates quick 5-second videos using the Gen-3 Alpha Turbo model based on prompts.
019d7601gen4 turbo
Creates high-quality video footage using the advanced Gen-4 Turbo model.
019d7601get organization
Retrieves your account details, including available credits and organizational billing information.
019d7601get task
Checks the status of a specific video generation job and provides the final output URL if it succeeded.
019d7601image text to video
Generates video by combining both an input image reference and a detailed text prompt to control motion.
019d7601image to video
Animates a static source image into a video clip, allowing you to specify the model and duration.
019d7601interpolate
Creates smooth motion footage by mathematically blending two distinct keyframe images together.
019d7601list tasks
Retrieves a list of your most recent video generation tasks, helping you track history and status.
019d7601text to video
Generates a video clip from scratch using only a text prompt, giving you control over the model and duration (5 or 10 seconds).
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
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Make Your AI Do More
Start with Runway ML, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Runway ML gives your AI agent direct access to high-end video tools. You'll generate, animate, and refine complex video clips—all without jumping between a bunch of different web portals.
Generating Video from Scratch
When you need a totally new scene, use text_to_video. This tool synthesizes an imaginative video clip using only your text prompt, giving you control over the model and how long it runs—you can specify 5 or 10 seconds. For quick cinematic sequences, call either gen3_turbo for fast 5-second clips or opt for gen4_turbo when you need high-quality footage from the advanced Gen-4 Turbo model.
Animating and Blending Footage
You can bring static pictures to life. Use image_to_video by providing a source URL, a model choice, and a duration; this animates that picture into a dynamic clip. If you need more control over the movement—say, guiding exactly how the camera moves or how the subject shifts—you'll use image_text_to_video. This tool takes both your reference image and detailed text prompts to guide the specific motion.
For super smooth transitions between two distinct keyframes, run interpolate. It mathematically blends those two images together, creating continuous, flowing motion footage.
Managing Your Jobs and Credits
Video rendering costs credits, so you gotta keep track of what's running. Use list_tasks to pull up a list of your most recent generation tasks, helping you see the history and current status. To check on one specific job, call get_task; this tells you if the render succeeded and gives you the final output URL if it did.
If things go sideways or you change your mind mid-render, use cancel_task to immediately stop the video job, saving your account credits. You can also check what kind of resources you've got left by running get_organization, which retrieves all your account details and billing info.
How Runway ML MCP Works
- 1 First, you enable the Runway ML integration and provide your secure Developer Portal token. This connects your AI agent to the video generation API.
- 2 Next, you prompt your AI client: 'Generate a 10-second clip of X using
gen4_turbo.' The agent then calls the specific tool and initiates the rendering task. - 3 Finally, you ask the agent to check status (e.g., 'What's the status for my last job?'). It uses
get_taskto report success/failure and provides the final MP4 link.
The bottom line is: You talk to your AI agent, it calls the right video tool, and you get a trackable task ID that leads to your finished footage.
Who Is Runway ML MCP For?
Creative Directors who need quick storyboarding; Marketing Content Managers needing B-roll assets fast; or Video Editors prototyping concepts without spending hours in complex software. If you're tired of juggling web portals, credit limits, and manual asset handoffs—this is for you.
Uses text_to_video or gen4_turbo to rapidly prototype full commercial sequences based on text prompts. They use it before writing a single line of script.
Employs image_to_video and image_text_to_video to generate eye-catching, high-grade B-roll quickly for platforms like Instagram or TikTok. They need volume, not perfection.
Uses task tools (list_tasks, get_task) and the billing check (get_organization) to ensure complex generation pipelines run within budget and complete on time.
What Changes When You Connect
- Stop context switching. You generate and manage videos—from
text_to_videoprompts to animating images withimage_to_video—all without leaving your agent interface. - Control costs immediately. If a render job is going over budget or off track, use
cancel_task. This saves you credits faster than checking the portal dashboard. - Go beyond simple generation. Need complex motion? Run
interpolateto create smooth transitions between two keyframes; it's much better than just cutting clips together. - Maintain full visibility into your work. Use
list_tasksand thenget_taskto check the status of a render, confirming if it succeeded and where the final video asset is located. - Flexibility in creation models. You get dedicated tools like
gen3_turbofor quick 5-second tests andgen4_turbofor your high-stakes, polished sequences.
Real-World Use Cases
Need to storyboard a commercial scene fast
A director needs five different angles of a futuristic city. They prompt their agent: 'Generate 5 clips using text_to_video with a cyberpunk theme.' The agent runs the tool multiple times, giving them five distinct task IDs they can review instantly, letting them prototype faster than ever.
Need to make an existing photo look cinematic
A user has a great reference photo but needs it animated. They ask their agent to run image_text_to_video using the URL and a prompt like 'Slow pan backwards.' The tool handles both the image input and the motion direction, delivering a ready-to-use clip.
Tracking expensive video renders
A producer runs three large videos. They don't know if they finished or how many credits were spent. Instead of logging into the website, they use list_tasks to see all history and then run get_organization to check their remaining credit balance.
Creating a seamless visual transition
A video editor has two key pieces of footage but needs them connected by a smooth motion bridge. They tell the agent to use the interpolate tool, providing the URLs for both images. The server outputs the perfect transitional clip.
The Tradeoffs
Running generation jobs manually
Logging into the Runway website, entering prompts into a form, clicking submit, and then leaving the site to wait for the render. This is slow, clunky, and involves multiple logins.
→
Just tell your AI agent what you want. Use text_to_video or gen4_turbo. The agent runs the job and gives you a task ID immediately. You don't have to wait on the website.
Forgetting to track credits
Running ten high-res videos without checking your account usage, only to find out later that you blew through your entire credit allocation.
→
Always check your limits first. Use get_organization before running any big batch of jobs. This keeps the pipeline running until you're ready for a top-up.
Assuming motion is free
Asking the agent to just 'make it move.' Without specifying both an image and a direction, the tool can't execute.
→
Be specific. For guided movement, use image_text_to_video and provide both the source URL and the descriptive prompt telling the motion path.
When It Fits, When It Doesn't
Use this server if you need to treat video creation as just another API call—like calling a database or sending an email. If your workflow requires generating, manipulating (via interpolate), and managing (via list_tasks) high-quality visual assets based on natural language prompts, this is it.
Don't use this if you need complex post-production features like color grading, audio mastering, or timeline editing within the AI agent. Those tools are separate. Also, don't expect the server to automatically figure out the best model; you often have to specify whether you want gen3_turbo or gen4_turbo. Always read the tool descriptions before making a request.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Runway ML API. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sourcing video assets used to require massive context switching.
Today, generating a single concept means jumping through hoops. You write the prompt in one interface, generate the clip on another website, and then you have to copy the URL and paste it into a third system just to manage billing or check its status. It's tedious clicking across half a dozen tabs.
With this MCP server, your agent handles the whole stack. You write the vision—say, 'Generate an alien sunset using `gen4_turbo`.' The AI runs the job and gives you a task ID right in the chat window. No browser jumps required.
Runway ML MCP Server: Generate cinematic video clips from chat.
You never have to worry about which tool is correct or how many parameters you're missing. You simply tell your agent what you need—a 5-second clip, an animated image, a transition—and the server calls the specific functions (`gen3_turbo`, `image_to_video`, etc.) for you.
This moves video production from a manual process to a single conversational step. Your workflow stays contained and predictable.
Common Questions About Runway ML MCP
How do I check if my generated video with the `text_to_video` tool is ready? +
You use the get_task tool, providing your task ID. The response will confirm status (like SUCCEEDED) and give you a direct MP4 link to download the finished clip.
Is there a way to stop a video job if I change my mind? +
Yes, use cancel_task. Just provide the task ID for the running job. This immediately shuts down the rendering process and saves your credits.
What's the difference between `image_to_video` and `image_text_to_video`? +
image_to_video animates a static image by giving it a duration and model. image_text_to_video is more advanced; you give it an image AND a directional prompt to control exactly how the camera or subject moves.
Can I check my video generation credits before running a big batch? +
Absolutely. Run get_organization. This tool pulls up your current account details, including how many credits you have left and your billing status.
What credentials do I need to connect my AI client before running a task with `gen3_turbo`? +
You must secure an API key from your Runway Developer Portal. This token authenticates your calls and ensures the server tracks usage against your account. Never share this key; it's required for all generation tools.
If a video job fails or encounters an error using `text_to_video`, how do I check the details with `get_task`? +
The get_task tool provides detailed status codes beyond just 'SUCCEEDED' or 'FAILED'. Check the output payload for specific error messages to diagnose why the render stalled, such as invalid prompts or resource limits.
Are there rate limits when I generate multiple videos in quick succession using `gen4_turbo`? +
Yes, Runway enforces usage tiers and API call limits. If you exceed your allocated quota, the server will return a specific HTTP 429 error code. You'll need to wait for the reset window or upgrade your subscription.
What image file formats does `interpolate` accept when creating smooth motion between two keyframes? +
interpolate requires both source images (keyframes) to be provided in common high-resolution formats like PNG or JPG. The system processes these inputs directly, so ensure they are correctly sized for the desired output resolution.
How can I preview the output without fully committing my prompt? +
Video generation actions using the Runway engines are directly invoked through asynchronous background tasks. Instead of an exact real-time preview, you can start small 5-second generations or iterate closely on your prompt texts until they produce the final aesthetic you want.
Does this integration process video rendering in real-time? +
No. Video rendering is asynchronous. When you submit a prompt or an image, the AI will dispatch a background task to Runway's servers and receive a 'task_id'. You will need to ask the AI to verify the status of this task later, usually after a few minutes, to fetch the final video URL.
Can I use Gen-4 models for free? +
No. Runway requires credits for all generations, and Gen-4 Turbo consumes significantly more credits than earlier models or standard actions. You must maintain sufficient active credits or a paid subscription on your Runway account for the AI to successfully execute the rendering jobs.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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