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Runware MCP

Runware API access for generating and processing images, video, audio, 3D assets, and text through MCP.

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Install Runware MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "mcp-203": {
      "command": "npx",
      "args": [
        "-y",
        "@runware/mcp"
      ],
      "env": {
        "RUNWARE_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

The install command started, but didn't respond the way we expected when we tried to talk to it.

npx -y @runware/mcp

initialize succeeded but no response to tools/list.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 21d ago.

Overview

Runware MCP MCP server exposes the Runware API to AI agents through tools for image, video, audio, 3D, and text tasks. It can execute inference jobs, inspect model schemas and metadata, search official or community models, manage media, and retrieve account or task information. The server runs through npm with stdio and requires a Runware API key. Reach for it when an agent needs to select Runware models, validate their parameters, and submit or inspect multimedia generation tasks.

Use cases

  • Generate images, video, audio, or 3D assets
  • Search curated and community model catalogs
  • Inspect model schemas, examples, metadata, and pricing
  • Store media for use as inference input
  • Check account usage and previous task results

Key features

  • Run Runware inference tasks across multiple media types
  • Discover official and community models
  • Validate model parameters with schemas
  • Manage stored media and custom model uploads
  • Retrieve account and task information

Tools12

What Runware MCP lets your agent do. Expand a tool for its parameters.

Self-reported~237 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

20/24 checks healthy over the last 90d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 1d ago via OSV.dev · @runware/mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

npm downloads1.5kPackage downloads in the last 30 days.
Last commit3d agoMost recent push to the default branch.
Install checkInconclusiveStarted but did not complete the MCP handshake in our test.
Tools exposed12Callable tools this server registers over MCP.
Directory activity2 viewsConfig copies, upvotes, and views on AllMCPs.

How Runware MCP works

What Runware MCP MCP server does

Runware MCP MCP server connects an MCP-compatible agent to the Runware API. It covers inference tasks across image, video, audio, 3D, upscaling, background removal, captioning, and other capabilities exposed by Runware models. The agent can ask for a result in natural language, while the server provides the API operations needed to select a model and submit the request.

The server also exposes discovery and account functions. An agent can inspect available capabilities, browse Runware’s curated model integrations, search the community catalog, review pricing, check account usage, and retrieve details from an earlier task.

How it works

The MCP process communicates with the agent over stdio. After connection, the agent chooses among the available tools based on the request. For example, it can use list_models to filter official integrations by capability, category, creator, or search term, then use model_schema to learn the parameters accepted by a selected model.

Before submission, parameters are checked against the model’s schema. This gives the agent feedback when a value does not match the selected model. Inference is submitted through run, which supports tasks such as generation, upscaling, and captioning on a specified model. Results from previous work can be inspected with get_task_details.

Setup and configuration

Install the package with either of these approaches:

  • Run it directly with npx -y @runware/mcp.
  • Install it globally with npm install -g @runware/mcp, then use the runware-mcp command.

A Runware API key from runware.ai is required. Set it in the RUNWARE_API_KEY environment variable. Claude Desktop can launch the server with the npx command and this environment variable; Cursor adds the same command and environment configuration through Settings → MCP → Add server. Codex can use the same MCP configuration.

Tools and capabilities

Runware MCP MCP server provides these tool groups:

  • run submits an inference task for a selected model.
  • model_schema returns a model’s parameter schema.
  • list_models, model_details, model_examples, and model_pricing describe curated Runware integrations.
  • list_capabilities lists capability identifiers and labels.
  • model_search searches community models, including Civitai fine-tunes and custom uploads.
  • media_storage stores or deletes images, video, audio, and 3D media for use as input.
  • model_upload uploads a custom model.
  • account returns account balance and usage information.
  • get_task_details returns the original request and response for an earlier task.

The model tools help an agent compare available integrations before calling run. Media storage is available when an input asset needs to be retained for a task.

Limitations and notes

The server requires a valid Runware API key, and the available operations depend on the Runware API and its models. Model parameters are not uniform, so the agent should inspect the relevant schema before submitting a task. The package is documented for npm-based installation and stdio use; the provided setup examples cover Claude Desktop, Cursor, and Codex.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Runware MCP

Runware MCP is an MCP server that connects AI agents to the Runware API for image, video, audio, 3D, and text tasks. Its main tools run inference, inspect model schemas, discover models, manage media, upload custom models, retrieve account data, and review previous task requests and responses.

Install it with `npx -y @runware/mcp` or run `npm install -g @runware/mcp` for a global installation. The global install provides the `runware-mcp` command. Set `RUNWARE_API_KEY` before starting the server.

Add the server to Claude Desktop’s MCP configuration with the npx command and set `RUNWARE_API_KEY` in the `env` section. A global installation can instead use the `runware-mcp` command.

Yes, Runware MCP works with Cursor through Settings → MCP → Add server. Use the same command and `RUNWARE_API_KEY` environment configuration described for the other clients.

Use `list_models` to browse curated integrations, `model_search` to search the community catalog, and `model_schema` to retrieve parameters for a specific model. Additional tools provide model details, examples, and pricing.

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