Runway ML MCP Server for VS Code Copilot 10 tools — connect in under 2 minutes
GitHub Copilot in VS Code is the most widely adopted AI coding assistant, embedded directly into the world's most popular code editor. With MCP support in Agent mode, Copilot can access external data and APIs to generate context-aware code grounded in real-time information.
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{
"mcpServers": {
"runway-ml": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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.
GitHub Copilot Agent mode brings Runway ML data directly into your VS Code workflow. With a project-scoped config, the entire team shares access to 10 tools. Copilot queries live data, generates typed code, and writes tests from actual API responses, all without leaving the editor.
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 VS Code Copilot 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 VS Code Copilot via MCP
Follow these steps to integrate the Runway ML MCP Server with VS Code Copilot.
Create MCP config
Create a .vscode/mcp.json file in your project root
Add the server config
Paste the JSON configuration above
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Start using Runway ML
Ask Copilot: "Using Runway ML, help me...". 10 tools available
Why Use VS Code Copilot with the Runway ML MCP Server
GitHub Copilot for Visual Studio Code provides unique advantages when paired with Runway ML through the Model Context Protocol.
VS Code is used by over 70% of developers. adding MCP tools to Copilot means your team can leverage external data without leaving their primary editor
Project-scoped MCP configs (`.vscode/mcp.json`) let you commit server configurations to your repository, ensuring the entire team shares the same tool access
Copilot's Agent mode integrates MCP tools seamlessly with file editing, terminal commands, and workspace search in a single agentic loop
GitHub's enterprise compliance and audit features extend to MCP tool usage, providing visibility into how AI interacts with external services
Runway ML + VS Code Copilot Use Cases
Practical scenarios where VS Code Copilot combined with the Runway ML MCP Server delivers measurable value.
Live API integration: Copilot can query an MCP server, inspect the response schema, and generate typed API client code in the same step
DevSecOps workflows: security teams can give developers access to domain intelligence tools directly in their editor for real-time vulnerability assessment during code review
Data pipeline development: Copilot fetches sample data via MCP and generates transformation scripts, validators, and test fixtures from actual API responses
Documentation generation: Copilot queries available tools and auto-generates README sections, API reference docs, and usage examples
Runway ML MCP Tools for VS Code Copilot (10)
These 10 tools become available when you connect Runway ML to VS Code Copilot 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 VS Code Copilot
Ready-to-use prompts you can give your VS Code Copilot 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 VS Code Copilot
Common issues when connecting Runway ML to VS Code Copilot through the Vinkius, and how to resolve them.
MCP tools not available
Runway ML + VS Code Copilot FAQ
Common questions about integrating Runway ML MCP Server with VS Code Copilot.
Which VS Code version supports MCP?
How do I switch to Agent mode?
Can I restrict which MCP tools Copilot can access?
Does MCP work in VS Code Remote or Codespaces?
.vscode/mcp.json work in Remote SSH, WSL, and GitHub Codespaces environments. The MCP connection is established from the remote host, so ensure the server URL is accessible from that environment.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 VS Code Copilot
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.