
Devicecloud
io.github.RubenGlez由 GitHub 帳號 RubenGlez 發布v0.3.3更新於 Nov 7, 2026
Triage failing DeviceCloud Maestro test runs: fail reasons, screenshots, flaky-flow analytics
概覽
唯讀 MCP 伺服器,把 DeviceCloud 上失敗的 Maestro 測試執行(失敗原因、截圖、報告與不穩定流程分析)帶進編輯器供排查。
- 可以做什麼
- 一次呼叫診斷某次執行:失敗流程、失敗原因、耗時、自動下載的失敗截圖,以及通過/失敗/不穩定彙總
- 依時間視窗評估套件健康度,把流程歸類為健康、不穩定、損壞或回歸
- 列出並依名稱或日期篩選近期上傳,讀取整體與各流程狀態及失敗原因
- 取得 JUnit XML 與 HTML 報告,並下載日誌、截圖、影片等原始產物
- 檢視各流程通過率分析,並深入查看單一流程檔案的執行歷史
- 適用情境
- 適用於 Maestro 流程透過 CI 在 DeviceCloud 上執行、希望助理直接讀取失敗證據並修正流程或應用程式碼而不必開啟儀表板的情境。也適合判斷哪些不穩定或損壞的流程值得優先修復。
- 執行需求
- 需要 Node.js 22 以上版本,透過 npx 隨需執行,無需另外安裝。需要 DeviceCloud API 金鑰,以環境變數 DEVICE_CLOUD_API_KEY 提供,並須在 shell 設定檔中匯出,讓子行程能繼承。需要連線 DeviceCloud REST API 的網路;解壓縮 HTML 報告還需要 unzip 指令。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Devicecloud,將其新增到工作區。
- 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
devicecloud-mcp
Triage failing DeviceCloud runs so your agent can fix them, without opening the dashboard.
When a DeviceCloud run goes red in CI, the reason why is buried in the web dashboard: the fail reason, the failure screenshot, the logs. This server pulls all of it straight into your editor, so your AI assistant (Claude Code, Cursor, Claude Desktop, etc.) can read the evidence, find the root cause, and fix the flow or app code. You commit, CI re-runs, and the dashboard stays closed.
DeviceCloud is a platform for running Maestro flows on real devices. Your CI triggers the runs; this server is how you debug the ones that fail.
It lets the assistant:
- diagnose a run in one call: failed flows, fail reasons, failure-screenshot paths, and a passed/failed/flaky summary, ready to act on
- rank suite health: classify every flow as healthy, flaky, broken, or regression over a window so you know what's worth fixing first
- list recent uploads, filter by name (commit message + short SHA) or date
- read per-flow status and
failReasonfor any upload - pull the JUnit XML report
- download and auto-unzip the HTML report (with failure screenshots highlighted)
- download raw artifacts (logs, screenshots, video) as a zip
- spot flaky vs genuinely-broken flows with per-flow pass-rate analytics
- drill into run history for a specific flow file
The server is read-only against the DeviceCloud REST API: no dcd CLI dependency, and nothing an agent does can trigger billable runs. Triggering and re-running tests stay with your CI; cancelling a run stays in the dashboard.
Install
Requires Node.js 22+ — check with node --version. There's no separate install step; the server runs on demand via npx.
Add this to your MCP client config:
Get your API key at console.devicecloud.dev/settings.
Claude Code: add it with one command
Skip editing JSON — register the server in one step:
Add -s user to make it available in every project instead of only the current one.
Configure your assistant
The config block above is the same for every client; only the file location differs.
Claude Code (project-scoped, .mcp.json)
Add to a .mcp.json at the root of any project where you want the tools available:
Then export the key from your shell profile so Claude Code's child process inherits it:
Setting it only in an interactive shell isn't enough; Claude Code spawns the MCP from its own environment, so the variable needs to be in the profile.
Claude Code (user-scoped, ~/.claude.json)
If you want it available everywhere instead of per-project, add the same devicecloud block under mcpServers in ~/.claude.json.
Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows). Restart Claude Desktop after saving; a tools icon appears in the chat input once the server connects.
Cursor
Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json at the project root (project-scoped).
Windsurf
Edit ~/.codeium/windsurf/mcp_config.json.
Other MCP-compatible clients
Any client that supports stdio MCP servers uses the same { command, args, env } shape. Consult the client's docs for the config file location.
Note: OpenAI products (ChatGPT, Codex, the Assistants API) use their own tool protocol and do not support MCP servers.
Verify
After restarting your assistant:
You should see a JSON-shaped response with an uploads array. If instead you get DEVICE_CLOUD_API_KEY env var is required, the variable isn't reaching the spawned process; re-check that it's exported from your shell profile (not just the current shell).
Available tools
Upload-naming convention
Uploads are typically named after the commit or build that triggered them. A common convention is to include the short SHA:
Filter with name = "*a1b2c3d4*" to find every upload for a specific commit. The wildcard is *, not %.
When uploads do and don't exist
DeviceCloud uploads are created when you trigger a run, via the CLI, a CI step, the GitHub Action, or the API directly. Whether a given commit has an upload depends entirely on your CI setup. If list_uploads returns nothing for a SHA you expect, the run probably wasn't triggered for that commit.
Troubleshooting
DEVICE_CLOUD_API_KEY env var is required: the variable isn't visible to the spawned MCP. Export it from~/.zshrc/~/.bashrc, restart your assistant.unzip failed(fromget_html_report): theunzipbinary is missing or crashed. Install withbrew install unzip(macOS ships with it; Linux usually does too).- HTTP 401 / 403: the API key is wrong or revoked. Regenerate it at console.devicecloud.dev/settings.
- Empty
list_uploadsfor your SHA: a run probably wasn't triggered for that commit. See "When uploads do and don't exist" above.
來源:README.md,提交 729d94d
工具
0版本歷史
2- v0.3.3最新Nov 7, 2026
- v0.3.2Sep 16, 2026
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