cascade-img

io.github.laffeyp由 GitHub 账号 laffeyp 发布v0.1.1更新于 Oct 24, 2026

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

发布方自己的服务:Ephemeris Time-Series Forecasting

概览

AI 生成的概览

让助手编写 Midjourney 提示词、通过 Discord 提交生成、用视觉检查返回的网格图、裁剪并清理最佳象限,并记录有效做法。

可以做什么
cascade-img 提供约 23 个 MCP 工具,覆盖完整图像流程:结构化提示词组合、提交 imagine 与视频任务、轮询状态、触发 Midjourney 操作(放大、变体、平移),以及接管用户在 Discord 中手动完成的结果。策展类工具可裁剪网格象限、去除背景、裁边、量化调色板、生成联系表和精灵表、用视觉为网格打分,并把优胜结果提升为最终输出。仅追加的提示词日志可跨会话保留,使每次运行都能读取此前尝试。所有调用都返回结构化的 ok/error 信封和稳定错误码。
适用场景
适合希望助手端到端完成 Midjourney 出图、而不是自己手写提示词并挑选象限的场景,尤其是重复批量、图标或精灵图制作,以及需要代理从早前尝试中学习的工作流。没有 Midjourney 订阅或希望使用官方受支持 API 的用户不适用。
运行要求
本地 Python 3.12+ 环境(从 PyPI 安装,用 uvx 运行),以及持续运行的 cascade-mj-bridge 守护进程,由它维持 Discord 连接。需要付费 Midjourney 订阅、一个已把 Midjourney 机器人加入频道的 Discord 账号,以及四个采集值:CASCADE_BRIDGE_URL、DISCORD_USER_TOKEN、MJ_CHANNEL_ID 和 MJ_IMAGINE_VERSION。仅支持桌面端;MCP 服务器本身未声明认证。
安装前请注意
它通过 Discord 用户账号自动化 Midjourney,README 说明 Discord 与 Midjourney 的服务条款都禁止用户账号自动化,使用风险自负。DISCORD_USER_TOKEN 是从 Discord 桌面应用采集的完整用户账号凭据,持有者可冒充该账号操作。守护进程必须保持运行并与 Discord 通信,提示词和任务活动会离开本机。生成会消耗付费 Midjourney 订阅额度。

安装

在 SourceWeft 中

  1. 打开 控制台中的 cascade-img,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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.

来源:README.md,提交 7c87496

工具

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版本历史

1
  1. v0.1.1最新Sep 16, 2026

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