Runware MCP

Runware MCP

MCP server that gives AI agents access to Runware's full API for image, video, audio, 3D, upscaling, and other media generation and processing tasks via natural language.

Category
Visit Server

README

Runware MCP

MCP server that gives AI agents (Claude, Cursor, Codex, etc.) access to the full Runware API — image generation, video generation, audio generation, 3D, upscaling, background removal, captioning, and more.

Install

Pick one — npx is simplest, global install is faster on repeat use.

# Use directly with npx (no install)
npx -y @runware/mcp

# Or install globally
npm install -g @runware/mcp

Connect

Get an API key at runware.ai. Then point your agent at the MCP.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "runware": {
      "command": "npx",
      "args": ["-y", "@runware/mcp"],
      "env": {
        "RUNWARE_API_KEY": "your-api-key"
      }
    }
  }
}

If you installed globally:

{
  "mcpServers": {
    "runware": {
      "command": "runware-mcp",
      "env": {
        "RUNWARE_API_KEY": "your-api-key"
      }
    }
  }
}

Cursor

Settings → MCP → Add server — same config as above.

Codex

Add to your MCP configuration with the same command and env.

How to use it

Once connected, just talk to your agent. It picks the right tool, picks the right model, and fills in the parameters.

  • "Generate an image of a cat in a forest"
  • "What models do you have for video generation?"
  • "Upscale https://example.com/photo.jpg by 4x"
  • "Show me my account balance"
  • "Find me a Civitai LoRA for anime style"

The agent figures out which model fits, what parameters to pass, and how to interpret the response. Parameters are validated against each model's schema before submission, so the agent gets fast feedback when it picks wrong values.

Tools the agent has access to

You don't call these directly — the agent does, based on what you ask for.

  • run — execute any Runware inference task (image, video, audio, 3D, upscaling, captioning, etc.) on a given model
  • model_schema — fetch the parameter schema for a specific model
  • list_models — list Runware's official, curated model integrations (supports capability, category, creator, search filters)
  • model_details — get full metadata for a curated model by AIR
  • model_examples — get sample input/output pairs for a curated model
  • model_pricing — get pricing overview + per-configuration examples for a curated model
  • list_capabilities — list every model capability (e.g. io:text-to-image, op:upscale) with labels
  • model_search — search the community model catalog (Civitai fine-tunes, custom uploads)
  • media_storage — store media (images, video, audio, 3D models) for use as input, or delete stored media
  • model_upload — upload a custom model
  • account — retrieve account information including balance and usage
  • get_task_details — retrieve the original request and response for a previous task

Environment variables

Variable Required Description
RUNWARE_API_KEY Yes Your Runware API key

Development

# Run directly (no build step)
npm run dev

# Build
npm run build

# Test
npm test

# Lint
npm run lint

# Smoke-test the stdio protocol
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"1.0.0"}}}
{"jsonrpc":"2.0","method":"notifications/initialized"}
{"jsonrpc":"2.0","id":2,"method":"tools/list"}' | RUNWARE_API_KEY=your-key node dist/index.js

# Or use the MCP Inspector for a UI
npx @modelcontextprotocol/inspector node dist/index.js

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured