Predictive Debugger

io.github.SpeedosDKPublished by GitHub account SpeedosDKv0.9.0Updated Oct 24, 2026

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

VerifiedSTDIODesktop onlyDeveloper Tools AI & ML

Server details

Identifier: io.github.SpeedosDK/predictive-debugger
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 24, 2026

Security note

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Overview

AI-generated overview

A local MCP server that helps coding agents predict where JavaScript and TypeScript code will fail at runtime, using static analysis plus an installed AI CLI.

What you can do: Rank source files by risk density and get complexity and risk metrics per file, excluding tests by default. Check TypeScript compiler diagnostics for selected files using local project settings. Map imports, reverse imports and connected test files with source-line evidence. Analyze logs for anomalies ranked by severity and unusual wording. Request an independent model verdict on likely failures with line number, reason and confidence, in batches. List which supported AI CLIs are installed and signed in.
When to use it: Useful when a coding agent is working on a JavaScript or TypeScript project and you want it to prioritize risky files, trace dependencies, or get a second opinion on where code may break before running it. Best suited to developers who already use Claude Code, Codex or GitHub Copilot CLI.
Requirements: Local process run via npx; requires Node.js 22 or later. Model predictions need at least one supported CLI (Claude Code, Codex or GitHub Copilot CLI) installed and signed in; Python 3 is optional for log analysis. No separate API key or environment variables are declared.

Before you install

The predict_failures tool sends source code and bounded dependency context to your CLI's model provider, consuming that CLI's usage allowance and subject to the provider's terms; calleeContext can be set to false to omit dependency context. Tools can read any path the server process can access, and project-scoped setup does not restrict file access. Risk scores and predictions can be wrong, and benchmarks do not establish accuracy on arbitrary repositories.

Installation

In SourceWeft

Open Predictive Debugger in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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:

On native Windows, from PowerShell:

powershell

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

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:

On native Windows, from PowerShell:

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": ["*"]    }  }}

{  "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:

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.

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
`check_types`	Return selected files' TypeScript compiler diagnostics using local project settings.	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 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:

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

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

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.

Source: README.md at commit 2f03938

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v0.9.0LatestSep 27, 2026
v0.8.2Sep 24, 2026

Score

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