A gallery of real-world usage stories: people driving Apache DolphinScheduler through an AI agent via dolphin-mcp-pilot, written up here and shared publicly (Xiaohongshu / RED, X, 掘金, CSDN, 知乎, Bilibili, YouTube, a personal blog, …).
Where examples/ collects reusable client configurations, cases/
collects what people actually did with them — the scenario, the conversation, the before/after,
and a link to the public post that tells the story.
A case is not a feature list — it is a short, honest story of a task you got done. The strongest cases share three things:
- A concrete task, not a demo for its own sake. "Our nightly ETL failed at 3am and I had the agent find the failed instances and rerun-from-failure from my phone" beats "I listed projects".
- The agent actually operating DolphinScheduler — a screenshot or short recording where you can see the natural-language request and the dolphin-mcp-pilot tool call / result. Read-only listing is fine as a supporting shot, but the interesting cases change state (create a workflow, fix a schedule, rerun a failed run).
- A public post other people can read, with the link recorded in your case file.
Pick one angle (or combine a few). These map to what dolphin-mcp-pilot is actually good at — see the tool list in the main README:
- 自然语言运维 / NL ops — operate DolphinScheduler in plain language from an MCP host (Claude Code, OpenClaw, Cursor, CodeBuddy, Claude Desktop). "Pause the sales-pipeline schedule, I'm doing maintenance."
- Incident firefighting — an instance failed; use the agent to read task logs, force a task success / skip a stuck task, or rerun-from-failure — end to end, without opening the DS console.
- One-line workflow creation — turn a sentence or a SQL snippet into a real SQL / DAG workflow, then bring it online.
- Schedule management by chat — create / online / offline / delete cron schedules conversationally, e.g. "move the daily report to 7am on weekdays only".
- Monitoring & morning-brief — have the agent summarize last night's runs, surface failures, and propose reruns.
- Version safety — roll back a workflow version or clone a workflow before a risky change.
- Multi-tenant / team — show per-request auth (
X-DS-TokenorX-DS-User/X-DS-Password) letting different teammates drive the same server with their own DolphinScheduler credentials. - Host integration write-up — a focused "how I wired dolphin-mcp-pilot into " walkthrough, with the gotchas you hit.
- Before / after — the same task done by hand in the DS web console vs. driven by the agent; what got faster or safer.
Bonus points for cases that combine dolphin-mcp-pilot with other tools in a real pipeline, or that teach a non-obvious trick (e.g. using the raw-API passthrough as a safety valve).
To keep the gallery trustworthy, every submission must meet all of these:
- Real usage. You actually ran dolphin-mcp-pilot against a DolphinScheduler instance. The case includes at least one screenshot or short recording showing the agent's request and the dolphin-mcp-pilot tool call / result. Mock-ups, staged screenshots, or unverified text do not qualify.
- A public post. The story is published on at least one public channel with an
openly reachable URL (no login-walled or private links). Record every link in the frontmatter
channels:list. The post should be substantive — a few sentences plus a visual, not a bare repost of this repo's README. - Original content. Your own writing and screenshots. No plagiarism, no AI-generated text passed off as a firsthand account. If you used AI to help draft the post, that's fine — just keep the events real.
- No secrets. Redact tokens, passwords,
X-DS-*header values, internal hostnames/IPs, and any private business data in every screenshot and config snippet. Use obvious placeholders. - This case file links back. The
README.mdyou submit here must link to the public post(s), so a reader can go from the gallery to the full story.
-
Fork this repository.
-
Copy
cases/TEMPLATE/tocases/<your-case-id>/(short, unique, kebab-case, e.g.nightly-etl-rerun). -
Fill in
README.md— complete the frontmatter and every section, and paste your public link(s). Addpreview.png(or more images) showing the agent operating DolphinScheduler. -
Open a Pull Request. Suggested title:
[case] <case-id> — <one-line what you did>
Multiple cases? One directory per case, one PR is fine.
cases/
├── README.md # this file — directions and requirements
├── TEMPLATE/
│ └── README.md # copy this to start a case
└── <your-case-id>/
├── README.md # required — frontmatter + the story + public links
├── preview.png # required — the agent operating DolphinScheduler
└── *.png / *.gif # optional — more screenshots
Each case README.md starts with YAML frontmatter:
---
title: Rerunning a failed nightly ETL from my phone
author: your-github-handle
date: 2026-08-14 # YYYY-MM-DD, when you published
category: incident-firefighting # one of the creative directions above
host: claude-code # the MCP host you used (claude-code / openclaw / cursor / codebuddy / claude-desktop / other)
testedWith: dolphin-mcp-pilot 0.2.0
channels: # one or more PUBLIC links to your published post(s)
- https://www.xiaohongshu.com/...
- https://x.com/...
---一个真实使用故事画廊:用户通过 dolphin-mcp-pilot、借助 AI 智能体来操作 Apache DolphinScheduler,把过程写在这里,并发布到公开渠道(小红书、X、掘金、CSDN、知乎、B 站、 YouTube、个人博客……)。
examples/ 收录的是可复用的客户端配置,cases/ 收录的是
大家真正用它做成了什么——场景、对话、前后对比,以及一条能读到完整故事的公开链接。
案例不是功能罗列,而是一个诚实的小故事:你用它把某件事做成了。最打动人的案例有三个共性:
- 一个具体任务,而非为演示而演示。"凌晨 3 点 ETL 挂了,我在手机上让智能体找到失败实例并 从失败处重跑",比"我列了一下项目列表"有力得多。
- 智能体真的在操作 DolphinScheduler——截图或短录屏里能看到自然语言请求 + dolphin-mcp-pilot 的工具调用/结果。只读列举可以作为辅助画面,但真正有意思的案例会改变状态 (新建工作流、修调度、重跑失败实例)。
- 一条公开帖子,别人能读到,链接记录在你的案例文件里。
任选一个角度(也可组合)。这些正好对应 dolphin-mcp-pilot 擅长的能力(见 主 README 的工具清单):
- 自然语言运维——在 MCP 宿主(Claude Code、OpenClaw、Cursor、CodeBuddy、Claude Desktop)里 用大白话操作 DolphinScheduler。"把销售管道的调度下线,我要做维护。"
- 故障救火——某个实例失败了:让智能体读任务日志、强制任务成功 / 跳过卡住的任务、或从失败处 重跑,全程不打开 DS 控制台。
- 一句话建工作流——把一句话或一段 SQL 变成真正的 SQL / DAG 工作流并上线。
- 对话式调度管理——会话式地 创建 / 上线 / 下线 / 删除 cron 调度,例如"把日报挪到工作日早 7 点"。
- 监控与晨报——让智能体总结昨晚的运行、暴露失败项、并建议重跑。
- 版本安全——高风险改动前回滚工作流版本或克隆工作流。
- 多租户 / 团队——展示逐请求鉴权(
X-DS-Token或X-DS-User/X-DS-Password),让不同同事 用各自的 DolphinScheduler 凭据驱动同一个 server。 - 宿主接入手记——一篇聚焦的"我如何把 dolphin-mcp-pilot 接进 <某 MCP 宿主>",含踩过的坑。
- 前后对比——同一个任务,DS 网页控制台手工做 vs 智能体驱动,快在哪、稳在哪。
加分项:把 dolphin-mcp-pilot 和真实流水线里的其他工具组合起来,或讲清一个不显而易见的技巧 (比如用 raw-API passthrough 当安全阀)。
为了让画廊可信,每份提交必须同时满足:
- 真实使用。你确实对一个 DolphinScheduler 实例跑过 dolphin-mcp-pilot;案例含至少一张截图或 一段短录屏,能看到智能体请求 + dolphin-mcp-pilot 工具调用/结果。臆造、摆拍、未经验证的文字不算。
- 公开帖子。故事发布在至少一个公开渠道、链接可直达(不能是需登录/私密链接);每条链接写进
frontmatter 的
channels:。帖子要有实质内容——几句话加一张图,而不是照抄本仓 README。 - 原创。自己的文字和截图,不抄袭,不拿 AI 生成的文字冒充第一手经历。用 AI 帮你润色文案没问题, 但发生的事情要真实。
- 不泄密。每张截图和配置片段都要打码 token、密码、
X-DS-*头的值、内网域名/IP、以及任何私有 业务数据,用明显的占位符替换。 - 案例文件要回链。你在这里提交的
README.md必须链接到公开帖子,读者能从画廊跳到完整故事。
-
Fork 本仓库。
-
把
cases/TEMPLATE/复制成cases/<你的案例 id>/(简短、唯一、kebab-case,如nightly-etl-rerun)。 -
填写
README.md——补全 frontmatter 和每个小节,贴上公开链接;加一张preview.png(或更多图) 展示智能体在操作 DolphinScheduler。 -
发起 Pull Request。建议标题:
[case] <案例 id> — <一句话你做了什么>
多个案例?一个案例一个目录,放在一个 PR 里也可以。
见上文英文部分的 Directory layout 与 Frontmatter。字段含义一致,category 取上面某个创作方向,
channels 至少一条公开链接。