# npm global
npm install -g aseprite-mcp

# or from source
git clone https://github.com/ayigityol/aseprite-mcp.git
cd aseprite-mcp && npm install && npm run build

{
  "mcpServers": {
    "aseprite": {
      "type": "local",
      "command": "node",
      "tools": ["*"],
      "args": ["/path/to/aseprite-mcp/build/index.js"],
      "env": { "ASEPRITE_PATH": "/path/to/aseprite" }
    }
  }
}

{
  "mcpServers": {
    "aseprite": {
      "command": "node",
      "args": ["/path/to/aseprite-mcp/build/index.js"],
      "env": { "ASEPRITE_PATH": "/path/to/aseprite" }
    }
  }
}

{
  "servers": {
    "aseprite": {
      "command": "node",
      "args": ["/path/to/aseprite-mcp/build/index.js"],
      "env": { "ASEPRITE_PATH": "/path/to/aseprite" }
    }
  }
}

{
  "mcpServers": {
    "aseprite": {
      "command": "aseprite-mcp"
    }
  }
}

sequenceDiagram
    participant Client as MCP Client
    participant Server as aseprite-mcp
    participant Aseprite as Aseprite CLI

    Client->>Server: Tool call (JSON-RPC via stdio)
    Server->>Server: Generate Lua script
    Server->>Aseprite: aseprite -b --script temp.lua
    Aseprite->>Aseprite: Execute Lua (headless)
    Aseprite-->>Server: stdout: __RESULT__{"success":true, ...}
    Server->>Server: Parse JSON, cleanup temp file
    Server-->>Client: Tool result

graph LR
    A[Tool Call] --> B{Thickness > 1?}
    B -->|Yes| C[app.useTool<br/>Native Brush]
    B -->|No| D[image:drawPixel<br/>Pixel Algorithms]
    C --> E[Save & Return]
    D --> E

# Build
docker build -t aseprite-mcp .

# Run (mount your Aseprite binary + working directory)
docker run --rm -i \
  -v /path/to/aseprite:/usr/local/bin/aseprite:ro \
  -v ./sprites:/sprites \
  aseprite-mcp

# Or use Docker Compose
docker compose up

npm run build       # Compile TypeScript
npm run watch       # Recompile on changes
npm test            # Run 74 unit tests (vitest)
npm run test:watch  # Watch mode
npm run inspector   # MCP Inspector for interactive testing