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

FronyBoard

de Cafelatte1versión 0.43.0i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.Cafelatte1/fronyboard

Instalar

Resumen

Descripción del creador (original en inglés)

Project tracker for AI agents: roadmap, periods, tasks and a validation gate, in one SQLite file

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: Bases de datos y conjuntos de datos

Instalación

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

Antes de instalar

Necesitas

  • PyPIuv de Python instalado (para el comando uvx)

¿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": {
    "fronyboard": {
      "command": "uvx",
      "args": [
        "fronyboard"
      ],
      "env": {
        "AIRA_DATA_DIR": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add fronyboard --env AIRA_DATA_DIR=your-value -- uvx fronyboard

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": {
    "fronyboard": {
      "command": "uvx",
      "args": [
        "fronyboard"
      ],
      "env": {
        "AIRA_DATA_DIR": "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": {
    "fronyboard": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "fronyboard"
      ],
      "env": {
        "AIRA_DATA_DIR": "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

  • AIRA_DATA_DIR env
    Data root; default is Frony/FronyBoard/data under LOCALAPPDATA (or ~/.Frony/FronyBoard/data)

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 8 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub Cafelatte1, 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 Bases de datos y conjuntos de datosi

  • Más estrellas que el 0% de los otros 1144 servidores de esta categoría
  • Publicado en el registro más recientemente que el 78% de los otros 1144 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 1144 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 FronyBoard?

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?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿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 (0.43.0) llegó al registro hace 9 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

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

Supabase

MCP server for interacting with the Supabase platform

de supabaseMuy usado↓ 235,4 mil/sem★ 3 milActualizado anteayer

Computadora o nube✓ supabase.com

MongoDB MCP Server

MongoDB Model Context Protocol Server

de mongodb-jsMuy usado↓ 157,1 mil/sem★ 1,2 milActualizado hace 3 días

Se ejecuta en tu computadora

Elasticsearch MCP Server

MCP server for interacting with Elasticsearch

de cr7258En crecimiento↓ 2,7 mil/sem★ 315Actualizado hace 14 meses

Se ejecuta en tu computadora

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.

FronyBoard

An MCP server that gives AI agents (Claude Code and friends) a first-class project tracker.

Where Jira is an issue tracker for humans behind a web UI, FronyBoard replaces each part with something an agent can use natively:

JiraFronyBoard
DatabaseOne SQLite file in a dedicated data directory
RecordsJSON documents (roadmap, period) + Markdown
APIMCP tools
Workflow engineSchema + rule validation, run as a gate before every write
State transitionAn MCP tool call (transition_task)

The schema and operating rules were extracted from a real product's management system (31 tasks shipped through it), then generalized.

Install

Requires uv. One line registers FronyBoard in Claude Code; uvx fetches the package from PyPI on first use and caches it:

claude mcp add FronyBoard -- uvx fronyboard

Any MCP client that can launch a stdio command works the same way — the command is uvx fronyboard. It is also listed in the MCP Registry as io.github.Cafelatte1/fronyboard. From a clone, point at the checkout instead (this needs git):

git clone https://github.com/Cafelatte1/fronyboard

claude mcp add FronyBoard -- uv run --directory \backend fronyboard

This is the local (stdio) mode: the client starts the server as a child process and talks to it over a pipe. No HTTP, no network, no credentials — web.py and fauth.py are never called. Data is written to %LOCALAPPDATA%\Frony\FronyBoard\data (~/.Frony/FronyBoard/data where LOCALAPPDATA is unset); set AIRA_DATA_DIR to relocate it. Logs (JSON Lines, one line per MCP tool call plus server events) go to the sibling logs folder — FRONYBOARD_LOG_DIR overrides.

To share one FronyBoard between several machines, or to use it from the Claude and ChatGPT apps, run it as an HTTP server instead — see docs/self-hosting.md.

Project setup

Connecting the MCP server gives every session the tools and the general workflow (delivered as server instructions). What it cannot know is which FronyBoard project a codebase belongs to — declare that in the codebase itself by adding this section to its CLAUDE.md (create the file if the project has none):

## FronyBoard

This project is tracked by FronyBoard (project key: DLY). Manage tasks through the FronyBoard MCP tools, following the FronyBoard server instructions.

Replace DLY with the project's key (register one first with create_project). The section is also the opt-in signal: a codebase without it is treated as not FronyBoard-managed.

Model

fronyboard.db

├── projects one row per project (key e.g. DLY): the roadmap record — │ yearly overview (goal / now / target / checklist) + quarterly milestones └── periods one row per opened period (e.g. 2026Q3): tasks ({KEY}-001, ...)

  • result (retrospective, written when the period closes)

A project is two kinds of records — the roadmap, and one record per period. Both are JSON documents; the schema and the rules that guard it are in backend/src/fronyboard/validation.py.

  • Task ids are a project-global sequence (DLY-042) — they keep counting across periods and are never reused. They are the only link between FronyBoard and a codebase: use them in branch names (feat/DLY-042/short-desc) and record the branch on the task.
  • A task is a title (v0.33.0, AIR-086) plus status, tags, depends_on, branch and two one-line notes of at most 300 characters each. Agents read titles and status; the 25-line body nobody read, and the month/week slots that only existed to schedule it, are gone. Time is meta.completed_at.
  • The two notes answer different questions at different moments (v0.38.0, AIR-090). content is written at create time and says why the task exists — the pressure behind it, or the scope deliberately left out. The approach chosen is not part of it (AIR-092): agents wrote it here and again in the commit, so it lives in the commit only. check is required by transition_task(status="done") and says what proves it done — the command and its output, or an observable a reader can go and see. One free note asked before the work can only restate the plan: in a 12-session benchmark every task an agent wrote paraphrased its own title, because the note was fixed at create time and update_task was never called. Reopening a task drops its check; nothing is proven any more.
  • Reference chain: period → roadmap milestone (the quarter). That is the only one, and the milestone is optional (v0.40.0, AIR-095): a period without one is valid, and its tasks are checked like any other's.
  • Statuses — milestones: planned | active | done; tasks: todo | in_progress | done | blocked | cancelled.
  • `cancelled` is the soft delete — there is no hard delete. Cancelling requires a reason, keeps the record (and its id) forever, and hides the task from queries by default (list_tasks takes include_cancelled). blocked = may resume, cancelled = will not happen; transitioning a cancelled task restores it.
  • Carry-over: a task that outlives its period is not moved — recreate it in the next period under a new id and note the mapping in the closing retrospective.
  • `get_status` is the whole resume — the overview, each period's open tasks, and recent_done: the ten most recently finished tasks with their content, their check and when they completed. What is already built is what a cold session needs most, and nobody makes a second call to find it (AIR-090). It is still a record of claims: the board says what an agent reported, the code is the evidence.
  • `depends_on` on a task lists the earlier tasks it builds on (other projects allowed). It points backwards only — there is no forward index, because storing one direction and deriving the other read as inverted often enough to be worth dropping (v0.36.0, AIR-089). The field was follows until v0.37.0; the boot migration renames it. It is a pointer, not a lock: list_tasks and get_status flag the entries not yet done as waiting_on, and nothing is ever blocked.
  • Timestamps (meta.created_at / updated_at / started_at / completed_at) are stamped by the server in naive UTC — started_at on the first in_progress transition, completed_at on done (and removed again if the task leaves done). Agents never write them.
  • The `result` field closes a period — the rest of the file holds only current state, so the "why it turned out this way" lives there: judgment and reasons, not counts. Its presence is what marks a period closed.

Tools

AreaTools
Projectscreate_project, update_project, list_projects, get_roadmap, get_status, validate
Roadmapset_overview, set_check, upsert_milestone
Periodsopen_period, close_period, get_retrospective
Planningcreate_task, update_task, transition_task
Querieslist_tasks, get_task, search_tasks, recent_activity
Guidehelp — the full usage guide as Markdown; the server instructions point to it

update_task and transition_task derive the project from the task id prefix (DLY-042 → DLY), so their key parameter is optional. Re-calling close_period on a closed period rewrites its retrospective.

Typical flow:

create_project

→ create_task (opens the current quarter) → transition_task in_progress (with branch) → ... → transition_task done → close_period (retrospective)

Planning is optional, not a prerequisite. create_task opens the current quarter by itself (in FRONYBOARD_TZ, else the server's zone); open_period opens any other quarter, with or without a milestone. set_overview and upsert_milestone add the year's and the quarter's goals whenever there are some. A milestone added to an open quarter starts active; closing the quarter marks it done.

Every mutation is validated before anything is written; invalid changes are rejected with the full error list. close_period refuses while tasks are still todo or in_progress. Writes are serialized per project, so concurrent clients cannot collide on ids or lose updates.

Self-hosting

The same package also runs as an always-on HTTP server (fronyboard serve): MCP over streamable HTTP for every machine on your network, a read-only web dashboard for humans, API keys per device, and OAuth for the hosted Claude / ChatGPT apps. Authentication is delegated to FronyAuth, a separate service. None of it is needed for the stdio install above. To see the dashboard on your own machine without any of that, run fronyboard serve --local (loopback only, no login) and open http://127.0.0.1:8642. docs/self-hosting.md covers the setup; docs/operations.md is the day-2 runbook.

Development

uv run --directory backend pytest      # backend

cd frontend; npm test # dashboard

The repo is a monorepo. backend/src/fronyboard/ — store.py (SQLite, data root), validation.py (schema gate), service.py (operations), auth.py (bearer middleware) + fauth.py (FronyAuth client), log.py, web.py (JSON API + static serving), server.py (MCP tool surface + CLI). frontend/ — the dashboard (React + Vite), built to static files that the backend serves; its build output frontend/dist is committed so a server needs no Node toolchain.

The three docs under docs/ cover what the code cannot tell you — running this on your own machines:

  • docs/self-hosting.md — running FronyBoard as a shared server: clients, dashboard, hosted apps, deploy
  • docs/operations.md — home server runbook
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