Runway ML MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Runway ML through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Runway ML, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Runway ML MCP Server
Connect your AI to Runway ML, the pioneer in applied AI research shaping the next era of art, entertainment and human creativity. This powerful integration empowers you to tap directly into Runway's cutting-edge Gen-3 Alpha and Gen-4 video generation models right from your conversational workspace. Produce stunning, realistic, or highly stylized video clips simply by typing out your vision or providing a reference image.
The Vercel AI SDK gives every Runway ML tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Text-to-Video Generation — Write detailed prompts to synthesize entirely new, imaginative scenes using
gen3_turbo,gen4_turbo, or the standardtext_to_videotooling. - Image-to-Video Animation — Bring still images to life using
image_to_videoor precisely guide the motion of a starting image with a textual director prompt usingimage_text_to_video. - Advanced Interpolation — Seamlessly blend two distinct keyframe images into one smooth transitional motion clip (
interpolate). - Complete Task Management — Maintain full control over costly generation pipelines. Easily check job status or output URLs (
get_task,list_tasks), cancel ongoing renders to save credits (cancel_task), and audit your organization's billing usage (get_organization).
The Runway ML MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Runway ML to Vercel AI SDK via MCP
Follow these steps to integrate the Runway ML MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Runway ML and passes them to the LLM
Why Use Vercel AI SDK with the Runway ML MCP Server
Vercel AI SDK provides unique advantages when paired with Runway ML through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Runway ML integration everywhere
Built-in streaming UI primitives let you display Runway ML tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Runway ML + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Runway ML MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Runway ML in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Runway ML tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Runway ML capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Runway ML through natural language queries
Runway ML MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Runway ML to Vercel AI SDK via MCP:
cancel_task
This action is irreversible. Cancels a running generation task
gen3_turbo
Quick 5-second video generation using Gen-3 Alpha Turbo
gen4_turbo
High-quality video generation using Gen-4 Turbo
get_organization
Retrieves Runway ML organization and credit details
get_task
Look for SUCCEEDED status and output URL. Retrieves the status and output of a generation task
image_text_to_video
Generates video from both an image and a text prompt
image_to_video
Specify source image URL, model, and duration. Animates a still image into a video
interpolate
Creates smooth motion between two keyframe images
list_tasks
Lists recent generation tasks
text_to_video
Specify prompt, model, and duration (5 or 10). Returns a task ID. Generates a video from a text prompt
Example Prompts for Runway ML in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Runway ML immediately.
"Create a 5 second cinematic video showing a sunset over an alien planet using Runway Gen-3 Turbo."
"Take this reference image URL and animate it with Gen-3 Turbo to make the camera slowly pan backwards."
"List all my ongoing tasks on Runway to see if the video has finished rendering."
Troubleshooting Runway ML MCP Server with Vercel AI SDK
Common issues when connecting Runway ML to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpRunway ML + Vercel AI SDK FAQ
Common questions about integrating Runway ML MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Runway ML with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Runway ML to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.