Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Source-backed public tables with citations, claim checks, and reviewable corrections.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
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Funciona en Claude para web, escritorio y móvil:
https://skeletable.com/mcpEjecuta esto en tu terminal
claude mcp add --transport http skeletable https://skeletable.com/mcpPégalo 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.
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:
https://skeletable.com/mcpLos 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.
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_tablesFind tables in the library. Each result gives its slug, the question it answers, its size and when it was last read.
get_tableRead 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_cellThe 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_claimTest 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_tableA 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_changeSuggest 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_tableMake 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_columnsAdd 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_rowsAdd 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_cellsSet 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_linkA 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_versionFreeze 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_tableCopy 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_instructionMake 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_cellsThe 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_cellsSave 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
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub eftpmc, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Respondió en 260 ms (HTTP 200)
No hace falta iniciar sesión
Leímos 16 descripciones de herramientas y no encontramos instrucciones ocultas para la IA
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
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.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.
El repo de GitHub cambió por última vez –, y la última versión (1.0.0) llegó al registro hace 5 días.
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.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Zoo MCP
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
An MCP server that provides access to the Zoo API for various CAD operations and tools.
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.
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.
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
| Tool | What it does |
|---|---|
list_tables | Find a table by what it covers |
get_table | Read a table: its scope, columns, a summary of each column, and its rows, live or as a saved version |
get_cell | One value's source, exact quote and date, or where we looked |
check_claim | Test a statement against a cell: it matches, differs, is disputed, or is unknown |
export_table | A table as CSV, live or a saved version, with chosen columns, and optionally each value's source, quote and origin |
propose_change | Suggest a new value with its proof, for the owner to review |
create_table | Make a private draft, ready to fill. proof: "optional" makes one for working data |
add_columns | Add columns to a draft, including AI columns with an instruction |
add_rows | Add up to 500 rows a call, each by name or with its values. A row it already has gets the new values |
fill_cells | Fill 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_link | A private CSV address for a notebook, script or spreadsheet, with the lines to load it |
save_version | Freeze a table as a numbered version with a link that never changes |
fork_table | Copy a public table, or one you run, into your account as a private draft |
set_instruction | Make a column an AI column, change its instruction, or clear it |
next_ai_cells | The next prompts for a table's AI columns, each with a fingerprint |
fill_ai_cells | Save the agent's answers to an AI column |
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:
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./owner/slug/v/2 and, for a public table, /data/owner/slug/v2.csv./d/ .csv load a private table into pandas or Google Sheets. ?columns=a,b picks columns and ?names=0 drops row names.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
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.
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.
Requirements: Node 22+ and pnpm 10 (corepack enable).
pnpm install
pnpm dev
| Command | What it does |
|---|---|
pnpm dev | Run the server on port 4200 |
pnpm dev:web | Run the site on port 5173, reading from that server |
pnpm test | Run tests |
pnpm lint | Lint |
pnpm typecheck | Type-check every package |
pnpm build | Production 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.