predictive-debugger

Predictive Debugger

Website and docs: predictivedebugger.dev

MCP server for finding likely runtime failures in JavaScript and TypeScript. Six tools help your coding agent 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.

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:

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

On native Windows, from 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:

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

On native Windows, from 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:

{
  "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 six tools. To check that the package downloads and print its version:

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

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

Tool	What it does	Model call
scan_project	Rank source files by risk density. Excludes tests by default.	No
analyze_file	Return complexity metrics, risk scores and contributing signals.	No
map_dependencies	Find imports, reverse imports and connected test files, with source-line evidence.	No
analyze_logs	Return log anomalies, ranked by severity and unusual wording.	No
predict_failures	Get an independent model verdict with a line number, reason and confidence. Supports batches.	Yes
list_providers	Check which supported CLIs are installed and their sign-in status.	No

Start with scan_project, then read the files it highlights. Use map_dependencies to find related files and predict_failures when you want a second opinion. Pass several paths as files to review them concurrently.

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:

Change	Requested check
One file, including a feature contained in one file	A fresh predict_failures call
Several files	A sub-agent scoped to the changed files and intended behavior, where the host supports it
Mechanical correction with one clear answer	Neither check required

Per-file predictions cannot verify that several files agree or that a feature meets its 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

• predictivedebugger.dev: website, quickstart and guides.
• Advanced setup: provider login, project scope, updates and local builds.
• Tool reference: parameters, prediction results, dependency context and scoring.
• VS Code preview: development host, commands and settings.
• Benchmarks and method.
• Development and contributing. Bug reports are welcome; code contributions are not open yet.
• Security policy. Report vulnerabilities privately.

License

MIT.