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PopNx MCPMCP servers for people who use AI · explained in plain words

Debugai MCP

by 1shizaanversion 2.9.0i★ –iRuns on your computer
Registry nameio.github.1shizaan/debugai-mcp

Install

Overview

Description from the maker (original English)

MCP server for DebugAI. Browser sign-in, auto client setup, no key pasting.

PopNx MCP’s three pillars

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

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: Web & browsers
  • You need to fill in: DEBUGAI_API_KEY

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).
  • You fill in yourself: DEBUGAI_API_KEY, DEBUGAI_API_BASE, DEBUGAI_TIMEOUT_MS, DEBUGAI_CONFIG_PATH

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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": {
    "debugai": {
      "command": "npx",
      "args": [
        "-y",
        "@debugai/mcp"
      ],
      "env": {
        "DEBUGAI_API_KEY": "your-value",
        "DEBUGAI_API_BASE": "your-value",
        "DEBUGAI_TIMEOUT_MS": "your-value",
        "DEBUGAI_CONFIG_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add debugai --env DEBUGAI_API_KEY=your-value --env DEBUGAI_API_BASE=your-value --env DEBUGAI_TIMEOUT_MS=your-value --env DEBUGAI_CONFIG_PATH=your-value -- npx -y @debugai/mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "debugai": {
      "command": "npx",
      "args": [
        "-y",
        "@debugai/mcp"
      ],
      "env": {
        "DEBUGAI_API_KEY": "your-value",
        "DEBUGAI_API_BASE": "your-value",
        "DEBUGAI_TIMEOUT_MS": "your-value",
        "DEBUGAI_CONFIG_PATH": "your-value"
      }
    }
  }
}

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": {
    "debugai": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@debugai/mcp"
      ],
      "env": {
        "DEBUGAI_API_KEY": "your-value",
        "DEBUGAI_API_BASE": "your-value",
        "DEBUGAI_TIMEOUT_MS": "your-value",
        "DEBUGAI_CONFIG_PATH": "your-value"
      }
    }
  }
}

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.

Values you fill in

  • DEBUGAI_API_KEY secret env
    Optional. Overrides browser sign-in (npx -y @debugai/mcp setup).
  • DEBUGAI_API_BASE env
    Optional. API base URL, for a staging or self-hosted setup. Defaults to DebugAI production.
  • DEBUGAI_TIMEOUT_MS env
    Optional. Deadline in milliseconds for a debug_error call. Defaults to 150000.
  • DEBUGAI_CONFIG_PATH env
    Optional. Alternate location for the config file that holds the stored key. Defaults to ~/.debugai/config.json.

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account 1shizaan, 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 Web & browsersi

  • More stars than 0% of the other 881 servers in this category
  • Published to the registry more recently than 98% of the other 881 servers in this category
  • Basic checks equal to or better than 100% of the other 881 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 Debugai MCP 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?

You need to fill in: DEBUGAI_API_KEY

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 (2.9.0) reached the registry today.

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: Browser Use, Chrome DevTools MCP, MCP Server Browser

Alternatives

Servers in the same category from other makers, sorted by stars.

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

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Lets AI use Chrome’s developer tools to inspect pages, find what makes them slow and spot errors. Made by the Chrome DevTools team.

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MCP Server Browser

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Install

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.

@debugai/mcp

Give your coding agent a debugger instead of a grep loop.

Your agent hands an error to debug_error and gets back the root cause, the exact file and line, and up to 3 ranked fixes as ready-to-apply edits. Each fix is labeled with whether a mechanical check actually passed, so the agent knows which ones were checked and which are the model's own estimate.

Before any of that, lookup_error asks your project's memory whether this error has happened here before and which fix held. It makes no model call and does not count against your limit, so an agent can afford it on every failure. In Claude Code a hook runs it for every failed command without the agent having to remember.

Auto-configures Claude Code, Claude Desktop, Cursor, Windsurf, Zed, Gemini CLI, and Cline. Works in any other MCP client with a manual entry. Node 18.14.1 or later.

New in 2.7.0: machine-applicable edits now name the file their code is actually in, the tools say to call them the moment something fails rather than waiting for you to paste an error, and a server that has fallen behind says so once per session instead of in the middle of every diagnosis. A server started in your home folder, a folder above it or the filesystem root no longer treats that as a project: it reads no local files until the agent names a projectRoot. See the changelog.

If a fix does not work, tell me and I will fix it. The fixes that did not work are how most of this release got written. [Dashboard → Messages](https://debugai.io/dashboard?tab=messages&src=npm-readme), with the error you sent and what the fix did instead. It reaches the person who builds this.

Setup

npx -y @debugai/mcp setup

That is the whole thing. It signs you in through your browser (no key to find or copy), writes the config for every MCP client it finds on this machine, then checks that all of it actually works.

Restart the clients it names and your agent has the tools.

Prefer to read first? debugai.io/start?src=npm walks the same thing per client.

What that command does to your machine

Worth knowing before you run something that edits your editor config:

  • Signs you in with a short code you confirm in the browser. Free account, 10 debugs a day, no card.
  • Stores your key in ~/.debugai/config.json with 0600 permissions. That is the only file that ever holds it.
  • Adds a debugai entry to the config of each MCP client it detects. Every file is backed up first ( .debugai-backup- ), every other setting in the file is preserved, and a file it cannot parse is left alone and reported instead. One caveat stated plainly: if your config contains comments, the rewrite drops them, because JSON has nowhere to put them. install writes first and tells you afterwards, and the backup still has them. install --dry-run tells you before anything is written.
  • Skips VS Code by default, because the DebugAI extension already registers this server there and a second entry would show every tool twice. install --client=vscode does it anyway if you want the server without the extension.
  • Never writes your key into a client config. Client configs get committed to repos. Keys should not.

Preview it without writing anything:

npx -y @debugai/mcp install --dry-run

Undo all of it:

npx -y @debugai/mcp uninstall   # removes the entry from every client config

npx -y @debugai/mcp logout # removes the stored key

Commands
CommandWhat it does
setuplogin then install, then verifies. The one you want.
loginBrowser sign-in. --key dbg_… to paste a key instead (CI, air-gapped boxes). --force to re-link.
logoutRemoves the stored key.
statusWhich key and account are active right now.
installWrites client configs. --list, --client=cursor, --all, --dry-run, --remove.
uninstallRemoves the entry from every client config.
doctorDiagnoses a broken setup: key, API reachability, per-client wiring, a config entry with no version, a key sitting in plain text in a client config.
hookThe Claude Code hook. Reads a failed command from stdin and prints what project memory knows. See Claude Code hook.

npx -y @debugai/mcp install --list prints every supported client, where its config lives on your OS, and whether DebugAI is already in it.

Signing in from inside a chat

If your agent calls a DebugAI tool before you have signed in, the tool answers with a short code and a URL instead of an error. Confirm it in the browser, tell the agent to try again, and the call goes through. No config editing, and no client restart, because the key is re-read on every call.

The tools

The loop they are built for: a command fails, lookup_error answers from memory in under a second, a confirmed fix is applied and the command re-run. When memory has nothing, debug_error does the analysis. Either way report_outcome says what happened, which is what the next lookup reads.

lookup_error

Has this project seen the error before, and what held? (2.6)

InputRequiredDescription
errorTextyesThe error or stack trace, as you would pass it to debug_error.
projectRootnoAbsolute path of the repository the error came from, when the agent was started somewhere else.
filePathnoAn absolute path inside that repository. Its git root names the project.

It is two small database reads and no model call, so it is free: it does not count against the debug limit (a separate, generous rate limit keeps it honest). It returns how many times the error was seen in this project and when, the stored fix and what state it is in, and fixes this project recently reported as failed:

  • confirmed: somebody applied it and said it worked. The answer says whether a live session watched the error stop or it was only accepted, because those are different amounts of evidence.
  • unproven: it was applied and the error has come back once since. Check it against the code as it is now.
  • anti-pattern: the error came back two or more times after it. The answer names it as the thing not to do.

A miss says so and points at debug_error. The text of the error is prepared exactly as a debug prepares it, credentials redacted first, so a lookup and a debug of one failure read the same memory row. A lookup writes nothing: it is not a debug and not a sighting.

debug_error

Give it an error, get an analysis.

InputRequiredDescription
errorTextyesFull error message, exception, or stack trace. A bug with no error text works too: say what you expected, what happened instead, and include the code in between.
languagenoauto (default), or name it: javascript, typescript, python, java, csharp, go, rust, cpp, c, php, ruby, kotlin, swift, lua, shell, powershell, sql, html, css, scala, dart, elixir, r, perl. Leave it on auto unless you have a reason: the server reads the error text and is right about it almost always. A name that is not on this list (markdown, cobol) is not an error: it is treated as auto.
codeSnippetnoUsually unnecessary, see below. Overrides the local read when given.
snippetStartLinenoWith codeSnippet: the line of the file that the first line of the snippet is. Pass it when the snippet is a window from the middle of a file. Without it the lines are counted from 1, and an error that says Line 44 cannot be matched to a 15-line snippet. (2.7)
filePathnoPath to the file that threw. An absolute path also names the repository the error belongs to.
projectRootnoAbsolute path of the repository, when the agent was started somewhere else. Project memory and local reads are scoped to it. (2.6)
reproCommandnoThe command that shows the failure: a test, a script, a curl. Fix #1 is aimed at making it pass, and each fix's check becomes this command instead of a syntax check. DebugAI never runs it. Up to 500 characters. (2.6)
expectednoWhat reproCommand should print or do once the bug is fixed. Up to 500 characters. (2.6)

Returns the root cause, up to 3 fixes ranked by confidence, the detected framework, and whether the answer came from cache. Each fix also carries, where derivable: edits (exact old/new strings your agent's edit tool can apply directly), unified_diff, and verify_with, the check to run after applying. With reproCommand that check is your command and the result you said to expect; without it, a syntax-level check. It never writes to your files and never runs your reproduction. Applying a fix is your agent's call, and yours.

An error longer than the 3,000 characters the API accepts is cut rather than refused: the start (where JavaScript, Java and .NET print the error) and the end (where Python prints it) are kept, the middle goes, and the answer says so. The same cut is made by lookup_error and the hook, so all three read one memory row for one failure. (2.6)

A footer on every answer names the project it was filed under, says when memory was off for it and why, and gives the version of this server and the engine build that answered. A session running on an old copy can see that it is, and an answer can be traced to the code that produced it. (2.6)

Every fix is labeled with its verification state, and there are three of them, not two: verified (a mechanical check passed, currently parse and import classes), failed check (confidence capped hard), or not verified (the confidence number is the model's own estimate, nothing checked it). We label the third case instead of hiding it.

It reads the source the trace names (2.2)

Paste a raw traceback and nothing else. This server runs on your machine, so it resolves the files in the stack trace and sends the relevant code along. Before 2.2 it could not, and an error pasted without code came back as *"Insufficient context for specific fix"* at 20% confidence. That was the common case, not the edge one.

The response names every file it read (Read locally: src/api.ts, src/db.ts, and local_files_read in the structured payload), so a wrong guess is visible rather than silent.

Exactly what it will and will not read:

  • Inside your project only. The boundary is your git repo root, or the working directory when that is not a repo. When that is your home directory, a folder above it or the filesystem root there is no boundary to read inside, so nothing local is read and the reply says so; pass projectRoot to name the project. It is checked *after* symlinks resolve, so a path in an error message cannot walk out of the project: ../../.ssh/id_rsa and a symlink pointing outside both fail the same check.
  • Source files only, by extension allowlist (.ts .tsx .js .jsx .mjs .cjs .py .pyi .go .rs .rb .java .kt .kts .scala .groovy .gradle .php .cs .swift .dart .c .cc .cpp .h .hpp .ps1 .psm1 .psd1 .vue .svelte). .env, .pem, key files, dumps and images are not on it, so they are never candidates.
  • Bounded: at most 3 files, none over 2 MB, and 50,000 characters in all. A large file is sent as a ±40-line window around the failing line rather than whole. Windowed blocks say so.
  • **Vendored code is sk

Only the beginning is shown; read the rest in the repo

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