Runware MCP
About
MCP server that gives AI agents (Claude, Cursor, Codex, etc.) access to the full Runware.ai API — image generation, video generation, audio generation, 3D, upscaling, background removal, captioning, and more.
Details
- Author
- runware
- Categories
- Other, AI
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Setup
Install Runware MCP in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/runware/mcp
Follow the installation instructions in the repository README, then restart your MCP client.
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.
Pick one —npxis 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
Get an API key atrunware.ai. Then point your agent at the MCP.
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" } } } }
{ "mcpServers": { "runware": { "command": "runware-mcp", "env": { "RUNWARE_API_KEY": "your-api-key" } } } }
Settings → MCP → Add server — same config as above.
Add to your MCP configuration with the same command and env.
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?"
- "Upscalehttps://example.com/photo.jpgby 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.
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 (supportscapability,category,creator,searchfilters)
- 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
# 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
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