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Skeletable

de eftpmcversión 1.0.0i★ –iSe ejecuta en la nube
Nombre en el registroio.github.eftpmc/skeletable

Instalar

Resumen

Descripción del creador (original en inglés)

Source-backed public tables with citations, claim checks, and reviewable corrections.

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 la nube
  • Transporte: Streamable HTTP
  • Categoría: Otros

Instalación

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

Antes de instalar

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://skeletable.com/mcp

Ejecuta esto en tu terminal

claude mcp add --transport http skeletable https://skeletable.com/mcp

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "skeletable": {
      "url": "https://skeletable.com/mcp"
    }
  }
}

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": {
    "skeletable": {
      "type": "http",
      "url": "https://skeletable.com/mcp"
    }
  }
}

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://skeletable.com/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.

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 6 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.

  • list_tables

    Find tables in the library. Each result gives its slug, the question it answers, its size and when it was last read.

  • get_table

    Read a table: its scope, its columns with the rule for each, a summary of what each column holds, and its rows. A null value is blank. `origins` says where a row's unquoted values came from, `ai` says how far each AI column has got, and `versions` lists saved versions. For a big

  • get_cell

    The evidence for one value: the source, the exact quote, what kind of source it is and when it was read. For a missing value, where we looked, and `absent` means the source was read and gives no such value. `url` is the cell's lasting address, showing its proof, for citing. `conf

  • check_claim

    Test a statement against one cell, such as whether a value in a draft or an answer is right. The verdict is `matches`, `differs` (with what the source states), `disputed` (sources disagree, see `conflicts`) or `unknown` (no acceptable source stated it, so say so). It compares val

  • export_table

    A table as CSV, ready to save as a file or load into a notebook. The first column is each row's name unless `names` is false. `columns` picks columns by id, in that order. With `proof`, each column is followed by its source and quote, and in a table whose proof is optional, by wh

  • propose_change

    Suggest a new value for a cell, with its proof. The quote must be word for word from the source and state the value. The owner reviews it before anything changes. Needs a token sent as a Bearer token.

  • create_table

    Make a private draft table, ready to fill, for anything from a tracker to a dataset. Its values say where they came from unless you set `proof` to `required`. Only `title`, `columns` and `rows` are needed now, but give `question`, `scope`, and a `rule` for each column if you can:

  • add_columns

    Add columns to a draft you run, such as a blank one a person started. Returns the new column ids for fill_cells. Needs a token.

  • add_rows

    Add up to 500 rows to a table you run. Each row is a name, or an object with its `values` by column id or label, so a whole tracker or dataset goes in a few calls. A row without a `key` gets the next free number. A name the table already has gets the values given for it, so synci

  • fill_cells

    Set up to 200 cells of a table you run. Usually a cell gives `value` and `origin` (`entered`, `imported` with a `note` like the file or email it came from, `link` with its `source`, or `generated`). Left out, the origin is `link` when there's a `source` and `generated` when there

  • data_link

    A private address that loads a table you run as CSV, for a notebook, a script or a spreadsheet, with the lines to do it. Add `?columns=a,b` to pick columns and `?names=0` to leave out row names. Anyone with the link can read the data, and `fresh` makes a new one so the old one st

  • save_version

    Freeze a table you run as it stands now, as a numbered version with a lasting link that never changes. Do this before training on a dataset or citing a table, and name the version you used. Needs a token.

  • fork_table

    Copy a table into your own account as a private draft, to extend or relabel: any published public table, or one you run. Every value keeps its proof or origin, and the copy remembers where it came from. Needs a token.

  • set_instruction

    Make a column an AI column, change its instruction, or turn it back into a plain column with an empty one. The instruction says what to work out for each row and names other columns in braces, like "Classify {Pitch} by genre". Its values never overwrite what a person typed, linke

  • next_ai_cells

    The next prompts to answer for a table's AI columns, up to 200 at a time: blank cells first, then answers whose row or instruction has changed. Answer each prompt yourself, then send the answers back with fill_ai_cells, each with its `row` and `basis`. Repeat until it says `done`

  • fill_ai_cells

    Save up to 200 answers to an AI column, each with the `row` and `basis` next_ai_cells gave it. An answer outside the column's choices, or to a prompt that has since changed, comes back with a reason. Each value is saved as generated, with the instruction and `model`. Needs a toke

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub eftpmc, 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

  • ✓ Superada

    El endpoint responde

    Respondió en 260 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 16 descripciones de herramientas y no encontramos instrucciones ocultas para la IA

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 32497 servidores de esta categoría
  • Publicado en el registro más recientemente que el 87% de los otros 32497 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32497 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 Skeletable?

Superó 3 de 3 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 la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (1.0.0) llegó al registro hace 5 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: Spec Driven Development, Remote Desktop Commander, Zoo MCP

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

Spec Driven Development

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MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
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Remote Desktop Commander

de desktop-commander

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

Se ejecuta en la nube★ 211Actualizado ayer
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Zoo MCP

de KittyCAD

An MCP server that provides access to the Zoo API for various CAD operations and tools.

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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.

Skeletable

Tables for people and agents, where every value records where it came from: a linked page, a person, a file or another app, or a model. Use one for a tracker, a dataset or a list. A new table works this way by default. A table can also require proof, as every table in the public library does: then each value links to the source and exact words that state it, or says where we looked. People read tables on the site, and agents read and build them through an MCP server.

Connect

The server takes MCP over HTTP at /mcp. Reading needs no account. Proposing a change or building a draft needs a token from Settings, sent as a Bearer token. An agent can only write to drafts its person runs, each value still passes every check, and a person publishes.

claude mcp add --transport http skeletable https://skeletable.com/mcp
ToolWhat it does
list_tablesFind a table by what it covers
get_tableRead a table: its scope, columns, a summary of each column, and its rows, live or as a saved version
get_cellOne value's source, exact quote and date, or where we looked
check_claimTest a statement against a cell: it matches, differs, is disputed, or is unknown
export_tableA table as CSV, live or a saved version, with chosen columns, and optionally each value's source, quote and origin
propose_changeSuggest a new value with its proof, for the owner to review
create_tableMake a private draft, ready to fill. proof: "optional" makes one for working data
add_columnsAdd columns to a draft, including AI columns with an instruction
add_rowsAdd up to 500 rows a call, each by name or with its values. A row it already has gets the new values
fill_cellsFill a draft's cells with proof, or say where you looked. Where proof is optional, a value can give its origin instead. Replies list only what failed
data_linkA private CSV address for a notebook, script or spreadsheet, with the lines to load it
save_versionFreeze a table as a numbered version with a link that never changes
fork_tableCopy a public table, or one you run, into your account as a private draft
set_instructionMake a column an AI column, change its instruction, or clear it
next_ai_cellsThe next prompts for a table's AI columns, each with a fingerprint
fill_ai_cellsSave the agent's answers to an AI column

Datasets

A table whose proof is optional is a dataset. Its values say where they came from: a linked page, a person, a file, or a model. On top of that:

  • AI columns have an instruction, like Classify {Pitch} as Horror, Puzzle or Racing. The person's own agent answers it for each row through next_ai_cells and fill_ai_cells, so Skeletable never runs a model itself. Each answer records the model and a fingerprint of its prompt, so a changed row shows its answer is out of date. A value a person typed is never overwritten.
  • Versions freeze a table with a lasting link, at /owner/slug/v/2 and, for a public table, /data/owner/slug/v2.csv.
  • Column summaries show what each column holds: categories with counts, text lengths, number ranges, and where values came from.
  • Data links at /d/ .csv load a private table into pandas or Google Sheets. ?columns=a,b picks columns and ?names=0 drops row names.
  • Forks copy a public table into your account to extend or relabel, and remember where they came from.

What's here

tables/          The tables, how they're scored, and their check results

packages/tables The table format and its checks apps/mcp The server: the MCP endpoint and the JSON the site reads apps/web The site, built with shadcn/ui and served by the server docker/ The server's image, which Railway builds

Licensing

The source code is licensed under Apache-2.0. Published table data is licensed separately under CC BY 4.0, as shown in the data responses.

Review table changes

Each table has Overview, Proposals, and History tabs, with an Open sheet button for the editor. Signed-in contributors can create a titled proposal with up to 20 cell changes, a reason, and a source and exact quote for each value. Bundles remain open for review, including when submitted by an owner. Existing single-cell owner saves still apply immediately after validation.

Account owners and editors can accept all changes in a bundle or close it. Acceptance is transactional and refuses a bundle if any cell has a newer version than the one recorded at submission. Close a stale proposal and submit an updated one. Accepted values remain in the existing version history. Discussion threads, revision restore, and editing an open proposal are not implemented yet.

Develop

Requirements: Node 22+ and pnpm 10 (corepack enable).

pnpm install

pnpm dev

CommandWhat it does
pnpm devRun the server on port 4200
pnpm dev:webRun the site on port 5173, reading from that server
pnpm testRun tests
pnpm lintLint
pnpm typecheckType-check every package
pnpm buildProduction build
pnpm tables validate Check a table's shape, numbers and text against its quotes
pnpm tables verify Open each source and look for every quote
pnpm tables watch See whether live quotes are still on their pages, and save the result
pnpm tables sample Draw a repeatable sample of cells for spot-checking

New tables start as JSON files in tables/, and the server loads them into Postgres when DATABASE_URL is set, or serves them directly when it isn't. It refuses to start if a table fails its checks.

Sign-in needs DATABASE_URL, GOOGLE_CLIENT_ID and GOOGLE_CLIENT_SECRET. PUBLIC_URL sets the site's address, and OWNER_EMAIL says who runs the official account.

Database tests run when TEST_DATABASE_URL is set. They wipe that database.

Pregunta a PopNx