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One command to install. Then your agent calls 40+ generation models, billed against your existing Avocado plan credits.\n\n## Install\n\n```bash\nnpm install -g @avocado-ai-co/cli\n```\n\nOr run without installing:\n\n```bash\nnpx @avocado-ai-co/cli auth login\n```\n\nRequires Node.js 18+. Tested on macOS; should work on Linux and Windows.\n\n## Quick start\n\n```bash\n# 1. Authorize this device (opens browser, signs you in once)\navocado auth login\n\n# 2. Install the Avocado MCP server into your editor\navocado mcp install --client claude-code   # or --client cursor\n\n# 3. Restart your editor and start generating from chat\n```\n\nFor Claude Code, the install command also drops a skill file at `~/.claude/skills/avocado.md` that teaches the agent to organize generated assets into local folders with manifests and captions, so you don't need to re-prompt the workflow each time.\n\nIn Claude Code, ask things like:\n\n> Using Avocado, generate a square 1:1 image of a green avocado wearing sunglasses.\n\n> Generate a 5-second video of a city skyline at sunset using Kling.\n\n> Use Avocado to create a 30-second voiceover of this script.\n\n## Generate from your terminal\n\nThe fastest path. No editor, no agent, just your shell:\n\n```bash\n# one-off\navocado generate \"a green avocado wearing sunglasses on a beach\" --out ./shots\n\n# pick the model, ratio, and count\navocado generate \"product packshot of a matcha can\" --model gpt-image-2 --aspect 16:9 --num 4\n\n# price it first, without spending\navocado generate \"...\" --num 4 --estimate\n\n# text-to-video (async; fetch later with: avocado job <id>)\navocado video \"a city skyline at sunset, slow drone push-in\" --model kling3-pro\n\n# interactive: run avocado with no command and start typing\navocado\n```\n\nImages are saved to disk (default: the current folder, created if needed) and billed against your plan credits. Run `avocado generate --help` for all flags, or `avocado --guided` to be walked through model, aspect ratio, and folder. Browse models with `avocado models`.\n\n## Commands\n\n| Command | What it does |\n|---|---|\n| `avocado` | Interactive mode: shows the splash, then prompts you for what to generate. Smart defaults; type `/guided` for model/aspect/folder, `/quit` to exit. |\n| `avocado generate \"<prompt>\"` | Generate an image and save it to disk. Flags: `--model`, `--aspect`, `--num`, `--quality`, `--out`, `--estimate`. |\n| `avocado video \"<prompt>\"` | Generate a text-to-video clip (async, 2-10 min). Flags: `--model`, `--aspect`, `--duration`, `--resolution`, `--out`, `--no-wait`. |\n| `avocado models` | List available image models with their credit cost. |\n| `avocado jobs` | List recent jobs you submitted from this device. |\n| `avocado job <id>` | Check a job and download its result if it's ready. |\n| `avocado auth login` | Opens your browser, mints a scoped API key, saves it to `~/.avocado/config.json`. |\n| `avocado auth logout` | Revokes the device's key on the server and clears local config. |\n| `avocado whoami` | Verifies the stored key by calling Avocado and printing your credit balance. |\n| `avocado mcp install --client <claude-code\\|cursor>` | Adds the Avocado MCP server to your agent's settings file. |\n| `avocado mcp uninstall --client <claude-code\\|cursor>` | Removes only the `avocado` MCP entry, leaving other servers intact. |\n| `avocado update` | Self-update to the latest version published on npm. |\n| `avocado --help` | Show all commands and options. |\n\nUse `--force` with `avocado mcp install` to overwrite an existing `avocado` entry. Pass `--no-skill` (Claude Code only) to skip the skill install.\n\n## Organized output (Claude Code)\n\nWhen you install on Claude Code, an Avocado skill is dropped at `~/.claude/skills/avocado.md`. It teaches the agent to:\n\n- Create a local folder per generation (e.g., `./avocado/<subject>/<YYYY-MM-DD>/`)\n- Download every returned URL to disk with descriptive, zero-padded filenames\n- Write `manifest.json` and `captions.md` for the batch\n- Poll long-running video jobs to completion before declaring done\n- Flag credit cost before large batches\n\nJust say: *\"Generate 5 product photos of my matcha latte using Avocado\"*, and the agent picks up the skill, organizes the output, and reports total credits spent.\n\nThe MCP server also exposes a `batch-generate-organized` prompt (image / video / music / sfx / speech) for explicit slash-command-style invocation.\n\n## What your agent can do\n\nOnce installed, your agent has access to these tools:\n\n- **Images**: `generate_image` (Nano Banana, SeedDream, Flux, Imagen, Recraft, Ideogram, GPT-Image), `edit_image`\n- **Video**: `generate_video` (Kling 2/3, Sora 2, Veo 3 / 3.1, Seedance 2.0, LTX-2, Hailuo, Vidu, WAN, Grok)\n- **Audio**: `generate_music`, `generate_sfx`, `generate_speech`\n- **Storyboards**: `create_storyboard`, `list_storyboards`, `generate_image_to_storyboard`\n- **Account**: `account_check_credits`, `check_job`, `models_list`\n\nAll generations are charged against your existing Avocado plan credits.\n\n## How auth works\n\n`avocado auth login` starts a one-time HTTP server on localhost, opens your browser to `https://www.avocadoai.co/cli/authorize`, and waits for the page to deliver a freshly minted API key over loopback after you approve. The key is saved to `~/.avocado/config.json` with mode `0600`.\n\nYou can revoke any key at any time from your Avocado account settings, or with `avocado auth logout`.\n\n## Links\n\n- Web: <https://avocadoai.co>\n- CLI docs: <https://avocadoai.co/cli>\n- MCP server: <https://mcp.avocadoai.co>\n\n## License\n\nMIT\n","readmeFilename":"README.md"}