Predictive Debugger

io.github.SpeedosDK由 GitHub 帳號 SpeedosDK 發布v0.9.0更新於 Oct 24, 2026

Predicts where JavaScript and TypeScript code will fail at runtime, for coding agents.

已驗證STDIO僅桌面開發者工具AI 與機器學習

概覽

AI 產生的概覽

一個本機 MCP 伺服器,透過靜態分析與已安裝的 AI CLI,協助程式設計助理預測 JavaScript 與 TypeScript 程式碼在執行階段會在哪裡出錯。

可以做什麼
依風險密度排序原始碼檔案,並提供每個檔案的複雜度與風險指標,預設排除測試檔。使用本機專案設定檢查所選檔案的 TypeScript 編譯器診斷訊息。整理匯入、反向匯入與相關測試檔,並附上原始碼行證據。分析日誌中的異常,依嚴重程度與異常措辭排序。批次要求獨立的模型判斷,給出可能出錯的行號、原因與信心程度。列出已安裝且已登入的支援 AI CLI。
適用情境
適合在程式設計助理處理 JavaScript 或 TypeScript 專案時使用,讓它優先關注高風險檔案、追蹤相依關係,或在執行前對可能出錯的位置取得第二意見。最適合已在使用 Claude Code、Codex 或 GitHub Copilot CLI 的開發者。
執行需求
透過 npx 執行的本機程序,需要 Node.js 22 或更新版本。模型預測需要至少安裝並登入一個支援的 CLI(Claude Code、Codex 或 GitHub Copilot CLI);日誌分析可選用 Python 3。未宣告個別的 API 金鑰或環境變數。
安裝前請注意
predict_failures 工具會將原始碼與有限範圍的相依上下文傳送給所用 CLI 的模型供應商,消耗該 CLI 的使用額度並受供應商條款約束;可將 calleeContext 設為 false 以省略相依上下文。工具可讀取伺服器程序能存取的任何路徑,專案層級設定並不會限制檔案存取。風險評分與預測可能出錯,基準測試無法證明其在任意程式碼庫上的準確性。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Predictive Debugger,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

[Predictive Debugger]

Predictive Debugger

Website and docs: predictivedebugger.dev

[npm version] [CI] [License: MIT] [GitHub stars]

MCP server for finding likely runtime failures in JavaScript and TypeScript. Seven tools help your coding agent check types, rank risky files, trace dependencies, inspect logs and get an independent model review with a line number and reason.

Uses the Claude Code, Codex or GitHub Copilot CLI you already have installed. Prediction calls use that CLI's model access and usage allowance. No separate API key is needed. Your provider's terms apply to those calls; check them before use, especially on a Claude subscription. See Provider terms.

Setup

Requires Node.js 22 or later. For model predictions, install and sign in to at least one supported CLI. Python 3 is optional for log analysis.

1. Add the MCP server

Choose your agent below. npx downloads and runs the package automatically.

Claude Code

Run in your project on macOS, Linux or WSL:

bash
claude mcp add --scope project predictive-debugger -- npx -y predictive-debugger@latest

On native Windows, from PowerShell:

powershell
claude mcp add --scope project predictive-debugger -- cmd /d /c npx -y predictive-debugger@latest

Use --scope user to make it available in every project.

Codex

For a user-level setup on macOS, Linux or WSL:

bash
codex mcp add predictive-debugger -- npx -y predictive-debugger@latest

On native Windows, from PowerShell:

powershell
codex mcp add predictive-debugger -- cmd /d /c npx -y predictive-debugger@latest

For project-only setup or a longer startup timeout, see Codex configuration.

GitHub Copilot CLI

Add to .mcp.json in your project:

json
{  "mcpServers": {    "predictive-debugger": {      "command": "npx",      "args": ["-y", "predictive-debugger@latest"],      "tools": ["*"]    }  }}

On native Windows, use "command": "cmd" and "args": ["/d", "/c", "npx", "-y", "predictive-debugger@latest"].

For every project, see Copilot user-level setup.

2. Check the connection

Restart your agent and check /mcp for predictive-debugger and its seven tools. To check that the package downloads and print its version:

bash
npx -y predictive-debugger@latest --version

Running without --version starts a stdio server that waits for your agent's messages. See setup help for local builds and troubleshooting.

3. Ask your agent about the code

text
Use Predictive Debugger to find the riskiest files in src/.Show the imports and tests connected to src/services/orders.ts.Check src/services/orders.ts for likely runtime failures.Find unusual entries in logs/app.log.

Tools

ToolWhat it doesModel call
scan_projectRank source files by risk density. Excludes tests by default.No
analyze_fileReturn complexity metrics, risk scores and contributing signals.No
check_typesReturn selected files' TypeScript compiler diagnostics using local project settings.No
map_dependenciesFind imports, reverse imports and connected test files, with source-line evidence.No
analyze_logsReturn log anomalies, ranked by severity and unusual wording.No
predict_failuresGet an independent model verdict with a line number, reason and confidence. Supports batches.Yes
list_providersCheck which supported CLIs are installed and their sign-in status.No

Start with scan_project and check_types, then read the files they highlight. Use map_dependencies to find related files and predict_failures when you want a second opinion. Pass several paths as files so small files share bounded model calls and avoid repeating the CLI context for every file.

See the tool reference for parameters, result fields and limits.

How the server asks agents to verify new code

The server's MCP instructions ask agents to check code they wrote in the current session from a fresh context. The routing depends on file count:

ChangeRequested check
One file, including a feature contained in one fileA fresh predict_failures call
Several filesA sub-agent scoped to the changed files and intended behavior, where the host supports it
Mechanical correction with one clear answerNeither check required

Grouped predictions retain per-file verdicts. They do not verify a feature's requirements. The benefit of the sub-agent rule has not been measured.

Privacy and limits

  • Static analysis, dependency maps and log analysis run locally. predict_failures sends source and bounded dependency context to your CLI's model provider. Set calleeContext: false to omit dependency context.
  • Credentials stay with the CLI. MCP tools can read paths the server process can access; project-scoped setup does not restrict file access. See the security model.
  • JavaScript and TypeScript are supported, including JSX, TSX and decorators. Vue and Svelte single-file components are not supported. Files above 4 MB are rejected; large predictions may cover only selected declarations.
  • Risk scores and predictions can be wrong. The benchmarks use development cases and do not establish accuracy on arbitrary repositories.
  • Manually verified on Windows. CI covers Windows, macOS and Linux on Node 22 and 24; real CLI installations on macOS and Linux have not been manually verified.

VS Code preview

An unfinished extension can show findings in the Problems panel. It requires a local build and is not available on the Marketplace or as a prebuilt VSIX. See trying the extension.

Documentation

License

MIT.

來源:README.md,提交 2f03938

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

2
  1. v0.9.0最新Sep 27, 2026
  2. v0.8.2Sep 24, 2026

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