{
  "mcpServers": {
    "openrouter": {
      "command": "npx",
      "args": ["-y", "@stabgan/openrouter-mcp-multimodal"],
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-..."
      }
    }
  }
}

{
  "mcpServers": {
    "openrouter": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-e", "OPENROUTER_API_KEY=sk-or-v1-...",
        "stabgandocker/openrouter-mcp-multimodal:latest"
      ]
    }
  }
}

npm install -g @stabgan/openrouter-mcp-multimodal

{
  "mcpServers": {
    "openrouter": {
      "command": "openrouter-multimodal",
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-..."
      }
    }
  }
}

npx -y @smithery/cli install @stabgan/openrouter-mcp-multimodal --client claude

Use chat_completion to explain quantum computing in simple terms.

Use analyze_image on /path/to/photo.jpg and tell me what you see.

Use search_models with capabilities.vision = true to find models that can see images.

Use generate_image with prompt "a cat astronaut on mars, digital art" and save to ./cat.png

src/
├── index.ts              # Server entry point, env validation, graceful shutdown
├── tool-handlers.ts      # Tool registration and routing
├── model-cache.ts        # In-memory model cache (1hr TTL)
├── openrouter-api.ts     # OpenRouter REST client (native fetch)
└── tool-handlers/
    ├── chat-completion.ts   # Text & multimodal chat
    ├── analyze-image.ts     # Vision analysis pipeline
    ├── generate-image.ts    # Image generation
    ├── image-utils.ts       # Sharp optimization, format detection, fetch
    ├── search-models.ts     # Model search with filtering
    ├── get-model-info.ts    # Model detail lookup
    └── validate-model.ts    # Model existence check

git clone https://github.com/stabgan/openrouter-mcp-multimodal.git
cd openrouter-mcp-multimodal
npm install
cp .env.example .env  # Add your API key
npm run build
npm start

npm test

docker build -t openrouter-mcp .
docker run -i -e OPENROUTER_API_KEY=sk-or-v1-... openrouter-mcp