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

DokuTrak

de Crackx17versión 0.1.2i★ 0iComputadora o nube
Nombre en el registroio.github.Crackx17/dokutrak-mcp

Instalar

Resumen

Descripción del creador (original en inglés)

Let your agent chase the documents: create, chase, read and collect DokuTrak Document Requests.

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: Computadora o nube
  • Transporte: stdio, Streamable HTTP
  • Categoría: Documentos, hojas de cálculo y oficina
  • Debes completar: DOKUTRAK_API_KEY

Instalación

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

Antes de instalar

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

Necesitas

¿Qué app usas?

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

Funciona en Claude para web, escritorio y móvil:

  1. Abre Settings → Connectors
  2. Presiona Add custom connector
  3. Pega la dirección de abajo y presiona Add
  4. Si te pide iniciar sesión, inicia sesión en el servicio del creador
SettingsConnectors1+ Add2https://…3
https://app.dokutrak.com/api/mcp

O ejecútalo en tu computadora

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "dokutrak": {
      "command": "npx",
      "args": [
        "-y",
        "dokutrak-mcp"
      ],
      "env": {
        "DOKUTRAK_API_KEY": "your-value",
        "DOKUTRAK_API_URL": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add --transport http dokutrak https://app.dokutrak.com/api/mcp

O ejecútalo en tu computadora

claude mcp add dokutrak --env DOKUTRAK_API_KEY=your-value --env DOKUTRAK_API_URL=your-value -- npx -y dokutrak-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": {
    "dokutrak": {
      "url": "https://app.dokutrak.com/api/mcp"
    }
  }
}

O ejecútalo en tu computadora

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "dokutrak": {
      "command": "npx",
      "args": [
        "-y",
        "dokutrak-mcp"
      ],
      "env": {
        "DOKUTRAK_API_KEY": "your-value",
        "DOKUTRAK_API_URL": "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": {
    "dokutrak": {
      "type": "http",
      "url": "https://app.dokutrak.com/api/mcp"
    }
  }
}

O ejecútalo en tu computadora

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "dokutrak": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "dokutrak-mcp"
      ],
      "env": {
        "DOKUTRAK_API_KEY": "your-value",
        "DOKUTRAK_API_URL": "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.

ChatGPT solo se conecta a servidores en internet:

  1. Abre ChatGPT en la web → Settings → Connectors (Apps)
  2. Presiona Create o Add (en algunos planes primero hay que activar Developer mode en Advanced)
  3. Pega la dirección de abajo, ponle un nombre y guarda
  4. Si te pide iniciar sesión, inicia sesión en el servicio del creador
SettingsConnectors1+ Create2https://…3
https://app.dokutrak.com/api/mcp

Los nombres de los menús pueden variar un poco según el plan y con el tiempo.

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

Valores que debes completar

  • DOKUTRAK_API_KEY secreto obligatorio env
    The Agent Connection, issued from Settings → Connect an agent in the DokuTrak app.
  • DOKUTRAK_API_URL env
    Base URL of the DokuTrak API, ending in /api. Defaults to https://app.dokutrak.com/api.

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

Nombres y descripciones de las herramientas tal como los informó el servidor el 8 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.

  • prepare_request

    Prepare or edit recipient, checklist, deadline and optional message before connecting. No request is created and nothing is sent. Keep the returned preview through connection, then pass it unchanged to review_request. Missing or invalid details must be corrected.

  • review_request

    After connection, submit the unchanged preview and a stable UUID operation_id. Open reviewUrl for the Professional to review and explicitly confirm in DokuTrak. Reuse the operation_id for retries. Changed details require a new operation and confirmation. No request or email is cr

  • send_request

    Send only after the Professional confirms the exact version on reviewUrl. Use operation_id and version from review_request. Retries recover the same request. sent means accepted by the email provider, not delivery to the inbox. delivery_unknown requires inspection in DokuTrak; do

  • get_request

    Read checklist receipt, Human Approval status, deadlines and recorded reminder progress. Give request_id or search the title, Client name or email. If several requests match, ask the Professional to select a candidate and call again with its id. Received does not mean approved. T

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 10 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub Crackx17, dueña del repo

  • ✓ Superada

    Sigue en mantenimiento

    Último cambio de código: hace 27 días

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • ✓ Superada

    El endpoint responde

    Respondió en 394 ms (HTTP 200)

  • – No aplica

    Inicio de sesión con OAuth

    No hace falta iniciar sesión

  • ✓ Superada

    Sin instrucciones ocultas en las descripciones de herramientas

    Leímos 4 descripciones de herramientas y no encontramos instrucciones ocultas para la IA

Comparado con otros en Documentos, hojas de cálculo y oficinai

  • Más estrellas que el 0% de los otros 3691 servidores de esta categoría
  • Publicado en el registro más recientemente que el 54% de los otros 3691 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 3691 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 DokuTrak?

Superó 4 de 4 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: DOKUTRAK_API_KEY

¿Se ejecuta en mi computadora o en la nube?

Funciona de las dos formas: instálalo en tu computadora o conéctate a la versión en la nube.

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez hace 27 días, y la última versión (0.1.2) llegó al registro hace 27 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.

¿Qué puedo usar en su lugar?

En la misma categoría: Puter MCP, Agent-Native Slides, Agent-Native Forms

Alternativas

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

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

Puter MCP

Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more

de HeyPuterMuy usado★ 44,1 milActualizado hace 5 meses

Se ejecuta en la nube✓ puter.com

Agent-Native Slides

Agent-Native Google Slides - generate and edit React presentations

de BuilderIOMuy usado★ 7,7 milActualizado hace 2 meses

Se ejecuta en la nube

Agent-Native Forms

Agent-Native form builder - create, edit, and manage forms

de BuilderIOMuy usado★ 7,7 milActualizado hace 2 meses

Se ejecuta en la nube

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.

dokutrak-mcp

The open MCP connector for DokuTrak: let your agent chase the documents.

DokuTrak collects documents from your clients on your behalf: you send a request, the client uploads through a secure link, the files are reviewed, and silent clients get reminded. This connector puts that loop inside the agent you already work in, so "where does the Dupont file stand?" is answered without leaving Claude.

The connector is a thin, stateless client of the DokuTrak API. It holds the Agent Connection you give it, stores nothing on disk, keeps no cache, and duplicates no rule: what your agent may and may not do is decided by the service, and refusals come back as tool errors with the service's own explanation.

Install

You need a DokuTrak workspace and an Agent Connection, issued from Settings → Connect an agent in the DokuTrak app. That screen hands you a paste-ready configuration with your key already in place; the instructions below are the same thing, by hand.

The key is read from the environment variable DOKUTRAK_API_KEY. It is never taken from the command line.

Install in Claude Desktop (one click)
  1. Download dokutrak.mcpb, the connector packaged as an MCP Bundle.
  2. Double-click it, or drag it onto Claude Desktop (Settings → Extensions).
  3. Click Install and paste your Agent Connection key when asked. Claude Desktop masks it, stores it securely and passes it to the connector as DOKUTRAK_API_KEY.

The bundle carries its own copy of the connector and runs on the Node.js built into Claude Desktop: no npx, no configuration file to edit. npm run bundle builds the same file from a clone.

Claude Desktop, by hand

Open the configuration file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the server under mcpServers (create the object if the file is empty):

{

"mcpServers": { "dokutrak": { "command": "npx", "args": ["-y", "dokutrak-mcp"], "env": { "DOKUTRAK_API_KEY": "dk_live_…" } } } }

Restart Claude Desktop. The DokuTrak tools appear in the tools menu of a new conversation.

Claude Code
claude mcp add dokutrak -e DOKUTRAK_API_KEY=dk_live_… -- npx -y dokutrak-mcp

Then /mcp inside Claude Code lists dokutrak and its tools.

Claude Code plugin: tax-season document chase
/plugin install dokutrak --marketplace Crackx17/dokutrak-mcp

The plugin adds the hosted connector (you sign in to DokuTrak on first use) and the tax-season-document-chase skill: give Claude your client list, it builds each client's checklist by return type (W-2, 1099, Schedule C, rental, K-1, retiree…), shows you the whole batch to confirm, prepares one request per client for you to confirm in DokuTrak, sends them, and later reports who is still missing what. Nothing goes out without your confirmation.

claude.ai and ChatGPT (hosted)

Add https://app.dokutrak.com/api/mcp as a custom connector. You sign in to DokuTrak (or create an account) during the OAuth step. The hosted connector prepares a request, sends it only after you confirm it in DokuTrak, and tracks progress. It never returns file content. Downloading files stays with this local connector. Setup: dokutrak.com/connectors.

From a clone, before the npm release
git clone https://github.com/Crackx17/dokutrak-mcp.git

cd dokutrak-mcp npm ci && npm run build

Then point the client at the built file instead of npx:

{

"mcpServers": { "dokutrak": { "command": "node", "args": ["/path/to/dokutrak-mcp/dist/cli.js"], "env": { "DOKUTRAK_API_KEY": "dk_live_…" } } } }

or, for Claude Code: claude mcp add dokutrak -e DOKUTRAK_API_KEY=dk_live_… -- node /path/to/dokutrak-mcp/dist/cli.js.

The skill

skills/dokutrak/SKILL.md teaches the agent the three everyday uses — ask a Client for documents, know where a request stands, chase on rejected files — and how to connect. It is what a DokuTrak user installs alongside the connector:

npx skills add Crackx17/dokutrak-mcp        # the open agent-skills installer

or by hand, for Claude Code / Claude Desktop:

cp -r skills/dokutrak ~/.claude/skills/dokutrak

Configuration

VariableRequiredDefaultMeaning
DOKUTRAK_API_KEYyes—The Agent Connection, from Settings → Connect an agent.
DOKUTRAK_API_URLnohttps://app.dokutrak.com/apiBase URL of the API. Ends in /api; the connector adds /v1.

Tools

Four tools, one round trip: ask, chase, know, collect.

create_request

Creates a Document Request and sends it, in one call, so nothing is left created but unsent. Takes the client's email, a deadline (YYYY-MM-DD or an ISO datetime), the checklist of documents wanted, and an optional title and message. The email goes to the recipient given here and to nobody else; the client uploads through the secure link it contains. Under the hood this is the same two-step the DokuTrak app performs: create with sendEmail: false, then send. If the send fails, the error names the created request, which stays visible in the dashboard.

Nothing goes out without your yes. The email to a real client cannot be recalled, so the tool tells the agent to show you the recipient, the deadline, the checklist and the message, and to wait for your confirmation. The tool is also flagged so that the client asks you before every call: Claude Code prompts each time, even in auto or bypass mode, and Claude Desktop treats it as a tool that always needs approval. A client that ignores these flags is left with the instruction to the agent alone.

request_replacement

Chases the client on the rejected files of a request: flags them, moves the request back to awaiting the client, and returns it to the automatic reminder cadence. This call sends no email by itself; the reminders do, and DokuTrak has no way to email the client immediately, not even from the dashboard. The optional message is recorded in the request's audit trail and is not sent to the client. It refuses a request with no rejected file.

get_request

Where a Document Request stands, in one call: status, the checklist, every collected file with its verdict (approved, rejected with the reviewer's reason, or pending), and the reminder state. Give a request_id, or a search term matching the title or the client's name or email. When several requests match, the tool returns the candidates and asks for the id.

download_documents

Every collected file of a request, as one zip archive. The archive comes back embedded in the tool result as binary content (an MCP resource with a base64 blob and application/zip), not as a link: the API has no short-link endpoint for a zip, and the connector writes nothing to disk. What the agent does with the bytes is decided on the professional's side, exactly like a download from the browser. Large archives make large results; check with get_request that documents have arrived before calling it.

What the connector cannot do

Approving or rejecting a document is your decision, taken in the DokuTrak dashboard. No tool here can take it, and the service refuses it to any Agent Connection regardless of which connector asks. The same goes for billing, workspace settings and the management of API keys.

Revoking the Agent Connection in DokuTrak takes effect on the very next call: the connector answers with the service's 401 and nothing else.

Privacy Policy

The connector runs on your machine and talks to one service only: the DokuTrak API (https://app.dokutrak.com/api, or the URL you set in DOKUTRAK_API_URL), with the Agent Connection you configured. It sends what the tools need (the request you create, the id or search term you look up) and relays the answers to your agent. It writes nothing to disk, keeps no cache or log, and sends no telemetry or analytics to DokuTrak or to anyone else.

Everything it sends is processed by DokuTrak under the DokuTrak Privacy Policy, which covers what is collected, how it is used and stored, the subprocessors it is shared with, retention and deletion, and your rights. Questions: arthur@dokutrak.com; security issues: security@dokutrak.com.

Development

npm ci

npm run check # typecheck, build, tests npm test # tests alone

The tests are contract tests at the MCP seam: a real MCP client and the real server, connected in memory through the official SDK's transport, with HTTP stubbed at fetch using recorded responses. They call tools, never functions, and run with no DokuTrak account and no network.

The staging run

Before a release, the built binary is driven once against a real workspace, by a real MCP client over stdio: create → chase → read → collect → revoke → 401. It is a record pasted into the release PR, never a CI check (a blocking check calls no third party). It pauses twice for acts the service refuses to any Agent Connection: rejecting the uploaded file, and revoking the key.

npm run build

DOKUTRAK_API_KEY=dk_live_… STAGING_RECIPIENT_EMAIL=you@example.com npm run staging

A real Document Request is created and a real email goes to STAGING_RECIPIENT_EMAIL. The transcript lands in staging-run- .md (git-ignored); the key is never written to it.

The MCP Bundle

npm run bundle builds mcpb/server/index.cjs (the connector with every dependency inlined), starts it and checks that it lists exactly the tools declared in mcpb/manifest.json at the version of package.json, then validates the manifest and packs dokutrak.mcpb with the official mcpb CLI. CI runs it on every pull request, and the release workflow attaches dokutrak.mcpb to the GitHub release of each tag. A change to the tool surface or the version updates mcpb/manifest.json too.

Releasing

A tag vX.Y.Z matching package.json and SERVER_VERSION triggers .github/workflows/release.yml: npm run check, npm publish (trusted publishing through GitHub's OIDC token, provenance attached), then the listing in the MCP Registry as io.github.Crackx17/dokutrak-mcp — the mcpName of package.json, which the registry checks against the published tarball. Running the workflow by hand does a --dry-run and publishes nothing.

License

MIT.

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