Predictive Debugger

Name: Predictive Debugger
Author: SpeedosDK

by SpeedosDKversion 0.9.0i★ –iRuns on your computer

Registry nameio.github.SpeedosDK/predictive-debugger

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "predictive-debugger": {
      "command": "npx",
      "args": [
        "-y",
        "predictive-debugger"
      ]
    }
  }
}

Run this in your terminal

claude mcp add predictive-debugger -- npx -y predictive-debugger

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "predictive-debugger": {
      "command": "npx",
      "args": [
        "-y",
        "predictive-debugger"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "predictive-debugger": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "predictive-debugger"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account SpeedosDK, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32433 servers in this category
Published to the registry more recently than 50% of the other 32433 servers in this category
Basic checks equal to or better than 100% of the other 32433 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Predictive Debugger safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.9.0) reached the registry 40 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Predictive Debugger

Website and docs: [predictivedebugger.dev](https://predictivedebugger.dev)

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:

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 seven 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
`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.

Predictive Debugger

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Symantec Cloud DLP AIops

README from the maker

Predictive Debugger

Setup

1. Add the MCP server

2. Check the connection

3. Ask your agent about the code

Tools

Privacy and limits

VS Code preview

Documentation

License