cascade-img

io.github.laffeyp由 GitHub 帳號 laffeyp 發布v0.1.1更新於 Oct 24, 2026

LLM-operable Midjourney pipeline: 21 MCP tools to compose, generate, curate with vision, and log.

發布方自己的服務:Ephemeris Time-Series Forecasting

概覽

AI 產生的概覽

讓助理撰寫 Midjourney 提示詞、透過 Discord 送出生成、用視覺檢查回傳的網格圖、裁切並清理最佳象限,並記錄有效的做法。

可以做什麼
cascade-img 提供約 23 個 MCP 工具,涵蓋完整影像流程:結構化提示詞組合、送出 imagine 與影片任務、輪詢狀態、觸發 Midjourney 動作(放大、變體、平移),以及接手使用者在 Discord 中手動完成的結果。策展類工具可裁切網格象限、去除背景、裁邊、量化調色盤、產生聯絡表與精靈表、用視覺為網格評分,並把優勝結果提升為最終輸出。僅可追加的提示詞日誌會跨工作階段保留,讓每次執行都能讀取先前的嘗試。所有呼叫都回傳結構化的 ok/error 信封與穩定錯誤碼。
適用情境
適合希望助理端到端完成 Midjourney 出圖、而不是自己手寫提示詞並挑選象限的情境,尤其是重複批次、圖示或精靈圖製作,以及需要代理從先前嘗試中學習的工作流程。沒有 Midjourney 訂閱或想使用官方支援 API 的使用者不適用。
執行需求
本機 Python 3.12+ 環境(從 PyPI 安裝,以 uvx 執行),以及持續執行的 cascade-mj-bridge 守護程序,由它維持 Discord 連線。需要付費 Midjourney 訂閱、一個已把 Midjourney 機器人加入頻道的 Discord 帳號,以及四個擷取值:CASCADE_BRIDGE_URL、DISCORD_USER_TOKEN、MJ_CHANNEL_ID 和 MJ_IMAGINE_VERSION。僅支援桌面端;MCP 伺服器本身未宣告驗證。
安裝前請注意
它透過 Discord 使用者帳號自動化 Midjourney,README 說明 Discord 與 Midjourney 的服務條款都禁止使用者帳號自動化,使用風險自負。DISCORD_USER_TOKEN 是從 Discord 桌面應用程式擷取的完整使用者帳號憑證,持有者可冒充該帳號操作。守護程序必須保持執行並與 Discord 通訊,提示詞與任務活動會離開本機。生成會消耗付費 Midjourney 訂閱額度。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 cascade-img,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[cascade-img — direct Midjourney by conversation: a director writes a prompt card, a helper robot carries it to a colossal artist robot forging framed paintings, and hands the cut-out winner back]

[CI] [PyPI] [License: Apache 2.0] [Python 3.12+] [MCP Tools: 23]

Generate Midjourney images by conversation instead of by hand. You describe what you want; your AI assistant composes the prompt, fires it, inspects the grid with vision, crops the best quadrant, cleans it up, and logs what worked.

You: "I need a flat-design mountain icon, centered, simple shapes, transparent background"
Agent: reads prompt log → composes prompt from parts → fires imagine →       waits → inspects 2x2 grid with vision → picks best quadrant →       crops it → removes background → saves → logs what worked

cascade-img is an MCP server with 23 tools that plugs into Claude, Cursor, Codex, or anything that speaks MCP. Midjourney is the first backend; Flux, DALL-E, and Imagen are on the roadmap. There's also a CLI.

Not a programmer? Open an AI assistant that can run commands (Claude Code, Cursor, or Cline), point it at this repo, and say: "Read RUNBOOK.md and set up cascade-img on this machine, then let me make images by describing them to you." It does the technical parts. You just need a Midjourney subscription and to copy a few values from Discord.


Quick Start

You need: a paid Midjourney subscription, a Discord account with the MJ bot in a channel, and Python 3.12 or newer.

bash
pip install cascade-img

Or from source:

bash
git clone https://github.com/laffeyp/cascade-imgcd cascade-img/packages/pythonpip install -e .

This puts three commands for operating cascade-img on your PATH: cascade-mj-bridge (the daemon), cascade-mcp (the MCP server), and cascade-mj (the CLI). Installing also adds a fourth command, cascade-trace-check — a diagnostics validator (not part of the generation loop) that replays a recorded event log and checks it against the vocabulary's declared event ordering and timing rules.

Configure — you need four values from the Discord desktop app (channel ID, server ID, imagine version, and your user token). Takes about five minutes. RUNBOOK.md walks through each one step by step.

bash
cp "$(python -c 'import cascade_img, pathlib; print(pathlib.Path(cascade_img.__path__[0]) / ".env.example")')" .env# Fill in the four values per RUNBOOK.md, then validate:cascade-mj-bridge --check-env --pretty

Start the daemon in one terminal, then connect from another:

bash
cascade-mj-bridge          # leave running — holds the Discord connection

Connect your AI assistant — add to your MCP config (Claude Desktop, Cursor, Cline):

json
{  "mcpServers": {    "cascade-img": {      "command": "cascade-mcp"    }  }}

Or point your assistant at this repo and ask it to read AGENTS.md — it'll wire everything up.

Or use the CLI:

bash
echo '{  "mountain-icon": {    "subject": "a flat-design icon of a mountain, centered, simple shapes",    "aspect_ratio": "1:1"  }}' > assets.json
cascade-mj mountain-icon --registry assets.json --upscale all --pretty

The 23 Tools

CategoryToolsWhat they do
Onboardingcascade_guideReturns the full operating manual in one call — the loop, every tool, the failure→action table. Call it first; the generation and curation tools are gated until it's read.
Generationimagine, generate_video, wait, status, bridge_health, mj_actionCompose and fire prompts, poll for results, check daemon health, trigger Midjourney actions (upscale, vary, pan)
Catch-upchannel_recent, adopt_messageSee what the human did by hand in Discord and claim those results into the pipeline — adopted messages become normal jobs that curation and mj_action work on
Compositioncompose_prompt, compose_videoBuild prompts from structured parts — subject, moodboard, style refs, aspect ratio, negatives — not freeform text
Curationcrop_grid, alpha_key, auto_trim, palette_quantize, contact_sheet, sprite_sheet, score_grid, video_filmstrip, loop_seam_delta, promoteExtract quadrants from grids, remove backgrounds, trim whitespace, build sprite sheets, score results with vision, promote winners to final output
Working memorylog_append, read_prompt_logAppend-only prompt log the agent reads before every run — what was tried, what worked, what didn't. Persists across sessions.

Every call returns {ok, result} or {ok: false, error: {code, remediation}}. Branch on the stable code, not the message. Full tool reference in AGENTS.md.


How This Differs

Other open-source Midjourney tools focus on the generation step — fire the prompt, hand back the image. cascade-img does the work around that:

  • Vision-based self-curation — the agent inspects its own output and picks the best quadrant
  • Structured prompt composition — prompts built from parts (subject, style, identity, constraints), not raw strings
  • Working memory — append-only log persists across sessions; each run reads what came before
  • Curation pipeline — crop grids, remove backgrounds, build sprite sheets, promote winners
  • MCP-native — 23 tools that plug into Claude, Cursor, Codex, or anything that speaks MCP
  • Pluggable backends — Midjourney now, Flux/DALL-E/Imagen on the roadmap

How It Works

One daemon, two stateless clients, all over local HTTP:

  • cascade-mj-bridge — the daemon. Only process that talks to Discord. Holds the live connection and tracks in-flight jobs. Must stay running.
  • cascade-mcp — the MCP server. Stdio by default (Claude Desktop / Cursor / Cline); --http <port> for HTTP. Stateless — start and stop freely.
  • cascade-mj — the CLI. Takes an asset ID and a registry, composes the prompt, fires, waits, writes to the log.

Prompts are composed from structured parts, not written as raw strings:

python
from cascade_img.prompt.composer import PromptComposer, Subject, StyleStack, IdentityStack
prompt = PromptComposer().compose(    Subject(        text="a flat-design icon of a mountain",        constraints=["centered", "simple shapes", "transparent background"],    ),    # Both optional. moodboard is a Midjourney personalization code;    # sref/oref are reference-image URLs you'd set up in MJ first.    style=StyleStack(moodboard="abc123def", sref="https://cdn.example.com/style.png"),    identity=IdentityStack(oref="https://cdn.example.com/ref.png", ow=1000),    aspect_ratio="1:1",    version="7",)

All three entry points emit structured JSON and follow the same {ok, result | error: {code, remediation}} envelope. Every failure carries a stable error code (e.g. DISCORD_401, MJ_UUID_MISSING, UPSCALE_BUTTON_FAILED) with a machine-readable remediation — so a caller branches on the code, not the message. The full catalog of log events and error codes is in vocabulary/0.1.json, and a trace checker (cascade-trace-check) enforces event ordering over recorded runs.

Midjourney terminology

prompt — the text + flags you send Midjourney. grid — the 2x2 set of four candidates returned per prompt. quadrant / U1-U4 — the four cells; "U2" means upscale the second. upscale — render one cell at full resolution. aspect ratio (--ar) — output shape. sref — an image whose style to borrow. oref — an image whose subject identity to keep across poses. moodboard (--p) — a saved personalization profile. stylize (--s) — how strongly MJ applies its own aesthetic.


Documentation

DocWhat it covers
AGENTS.mdThe LLM operator's guide. Read this when handing cascade-img to an agent.
RUNBOOK.mdInstall, env capture, setup, reconnect lifecycle, every failure mode with error codes and fixes.
CAPABILITIES.mdEvery Midjourney feature cascade-img drives — prompt parameters, mj_actions, the V8.1/V7 split.
ARCHITECTURE.mdInternal architecture and design decisions.
examples/Three walkthroughs: single image, batch, video. Read AGENTS.md first.
CHANGELOG.mdRelease history.

Roadmap

VersionWhat's in it
v0.1 (current)MJ backend (V8.1 + V7), prompt composer, curation tools, MCP server, CLI, prompt log
v0.2Channel catch-up + message adoption — landed on main: channel_recent and adopt_message let the agent see what the human did by hand in Discord and act on it (design); still to come: more MJ commands (/describe, /blend, Vary Region inpaint, /tune), retro-U-press on adopted grids, internal refactoring
v0.3TypeScript wrapper; first API backends — Flux via Fal + Flux Kontext, Ideogram
v0.4Google Imagen, Recraft (native vector/SVG)
v0.5OpenAI gpt-image, Stable Diffusion
v1.0API stable, three+ backends in production

Every backend implements one interface, so a later release can chain them — generate on one provider, refine on a second (e.g. Flux Kontext), upscale on a third.


Repository Layout

cascade-img/├── packages/python/        # the Python package (cascade_img)│   ├── src/cascade_img/    #   prompt/, interfaces/, backends/, curation/, vocabulary/│   ├── tests/              #   behavior tests│   └── tools/              #   live smoke walk├── examples/               # three walkthroughs of the operating loop├── vocabulary/0.1.json     # event log-line catalog└── *.md                    # README, ARCHITECTURE, RUNBOOK, AGENTS, CAPABILITIES, ...

Disclaimer

This tool automates Midjourney through a Discord user account. A paid Midjourney subscription is required. Both Discord and Midjourney's Terms of Service prohibit user-account automation. This is the same mechanism used by every open-source MJ tool (midjourney-proxy, midjourney-api, etc.) — there is no public Midjourney API. Use at your own risk.

The backend interface is pluggable — Flux, DALL-E, and Imagen are on the roadmap.

License

Apache-2.0. See LICENSE.

來源:README.md,提交 7c87496

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  1. v0.1.1最新Sep 16, 2026

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