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PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

Debugai MCP

de 1shizaanversión 2.9.0i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.1shizaan/debugai-mcp

Instalar

Resumen

Descripción del creador (original en inglés)

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

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Web y navegadores
  • Debes completar: DEBUGAI_API_KEY

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

  • Revisiones básicas: 1 de 1 superadas
  • Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
  • Debes completar tú: DEBUGAI_API_KEY, DEBUGAI_API_BASE, DEBUGAI_TIMEOUT_MS, DEBUGAI_CONFIG_PATH

Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en 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"
      }
    }
  }
}

Ejecuta esto en tu 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

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.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"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "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"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • DEBUGAI_API_KEY secreto 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.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub 1shizaan, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Web y navegadoresi

  • Más estrellas que el 0% de los otros 880 servidores de esta categoría
  • Publicado en el registro más recientemente que el 99% de los otros 880 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 880 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Debugai MCP?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

Debes completar: DEBUGAI_API_KEY

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (2.9.0) llegó al registro hoy.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Browser Use, Chrome DevTools MCP, MCP Server Browser

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Browser Use

de browser-use

Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.

Computadora o nube★ 120.087MITActualizado hace 17 días
Instalar

Chrome DevTools MCP

de ChromeDevTools

MCP server for Chrome DevTools

Se ejecuta en tu computadora★ 54.821Apache-2.0Actualizado hace 15 días
Instalar

MCP Server Browser

de bytedance

MCP server for browser use access

Se ejecuta en tu computadora★ 39.550Apache-2.0Actualizado hace 14 meses
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

@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

Solo se muestra el principio; lee el resto en el repo

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