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runway-dev-models

runway-dev-models

github.com/runwaymlDevelopment74732 installsUpdated 2d ago
Repository

About runway-dev-models

Guidance for developers integrating Runway Dev models into an app, keeping requests behind its server boundary and following endpoint-specific documentation for inputs, tasks, and outputs.

Key features

  1. 01Inspect existing app input and output flows
  2. 02Use Dev MCP to look up models
  3. 03Consult current endpoint documentation
  4. 04Create and wait for tasks with the official SDK
  5. 05Validate inputs and handle errors and credentials

Use cases

  1. 01Add Runway models to an app's existing flow
  2. 02Select endpoints based on project access and constraints
  3. 03Handle uploads, temporary output URLs, and API secrets safely

MCP support

The workflow uses Dev MCP's `list_models` to look up models for a relevant project and endpoint when selection or access constraints matter. It also notes that Dev MCP uses OAuth separately from the app's `RUNWAYML_API_SECRET`.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/runwayml/skills --skill runway-dev-models

After installing, type/runway-dev-modelsin Claude Code to confirm it loaded.

Details

From the project README

Runway Dev models

Integrate a direct model endpoint into the application's existing server and user flow. Consult runway-dev for account setup, credential boundaries, and shared SDK guidance when that skill is installed.

Workflow

  1. Inspect the app and determine where users provide inputs and consume outputs. Keep Runway requests behind the app's server boundary.
  2. Honor a model the user or existing app explicitly selected. If a model must be selected or current project access and constraints matter, use Dev MCP's list_models for the relevant project and endpoint. Never guess a project ID or infer access from a model name. For catalog summaries, preserve each endpoint's returned price units and constraints, and verify model counts against the full response.
  3. Read the exact current endpoint reference from https://docs.dev.runwayml.com/llms.txt and https://docs.dev.runwayml.com/api.md. A model's fields, allowed values, inputs, and outputs can differ from other models; copy no schema from a neighboring endpoint.
  4. Use the official SDK for the app's language. For task-creating calls, chain waitForTaskOutput() or wait_for_task_output() from the unawaited create() response. Handle documented task errors and let the user inspect or recover the task rather than silently submitting it again.
  5. Wire success, loading, and error states into the existing interface. Treat signed output URLs as temporary; persist media if the application needs it later.
  6. Run appropriate local validation. A live generation is billable: perform one only when requested or approved, and check the selected project's credit balance immediately beforehand.

Inputs and credentials

Follow the current input documentation for HTTPS URLs, data URIs, and upload URIs. For browser-selected files, send the file to the application's server and use the SDK's documented upload flow. Do not pass local filesystem paths to the API or accept arbitrary client-supplied remote URLs without validation.

Keep RUNWAYML_API_SECRET on the server in the project's existing secret mechanism. Never expose it to browser code or place it in MCP configuration; Dev MCP uses OAuth separately.

Current docs

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