Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Convert DOCX/XLSX to Markdown — native chart-data extraction, optional VLM for figures
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.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿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": {
"refigure": {
"command": "uvx",
"args": [
"refigure"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add refigure -- uvx refigurePégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"refigure": {
"command": "uvx",
"args": [
"refigure"
]
}
}
}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": {
"refigure": {
"type": "stdio",
"command": "uvx",
"args": [
"refigure"
]
}
}
}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.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub HelgDemidov, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
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 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.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
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).
El repo de GitHub cambió por última vez –, y la última versión (0.3.5) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Dialyne
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.
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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.
Converters where figures survive.
DOCX/XLSX → Markdown that keeps charts and infographics machine-readable instead of losing them to OCR or a vision model: native OOXML chart data (numCache/strCache) recovers exact numbers with zero GPU calls, zero VLM calls, zero lost precision — by default, not as a fallback.
That default path is also why the base install (pip install "refigure[docx,xlsx]") is ~500x lighter than PyTorch-based alternatives (5.6MB vs. multi-GB) — the core conversion needs no ML model at all. That number is about the core architecture, not every distribution format: the Docker image trades it back deliberately, bundling VLM providers + LibreOffice for a turnkey composite-figure path (see Docker below).
VLM interpretation itself is there for the rare figure with no native data at all (a dashboard screenshot) — never required just to get real numbers out of a chart, on any distribution format.
Ships as a library, CLI, MCP server, and a one-click Claude Desktop bundle — every surface returns the same native-fidelity output, not a degraded summary for agents.
numCache/strCache directly; no rasterize/OCR/VLM step for charts, real numbers every time.[vlm] extra, --vlm/Config(use_vlm=True)) — cloud description + a real rendered mermaid diagram (26 supported diagram types — flowcharts, pie/xy charts, sequence/state/ER diagrams, Gantt/timeline/sankey/treemap and more, see Status below) on top of the zero-loss floor, for figures with no native chart data at all (e.g. a dashboard screenshot). Provider-agnostic — OpenRouter by default, or direct OpenAI/Ollama/vLLM/LM Studio/Anthropic via --vlm-provider ([vlm-direct] extra). --strict upgrades one specific failure (the system soffice/LibreOffice binary missing) from a graceful skip to a hard error; every other VLM failure still degrades.ConversionResult (markdown + warnings + chart/group counts + vlm_used), not a bare string.refigure console command, stdin/stdout-first, native batch mode, typed exit codes (see below).refigure-mcp console command ([mcp] extra), stdio or Streamable HTTP, tools/resources/prompts, batch conversion with per-file isolation (see below).ghcr.io/helgdemidov/refigure, both console commands on PATH, soffice/LibreOffice baked in — the VLM composite-figure path works turnkey, no manual LibreOffice install. Multi-arch — linux/amd64 + linux/arm64, native Apple Silicon (see below).docx+xlsx only, see below).Optional VLM interpretation — for a figure with no native chart data at all (a screenshot, not an OOXML chart part) AND no matching mermaid construct either (a dense radial sunburst — nothing in the 4 original mermaid types could represent it), --vlm both recovers the real content and produces a genuinely renderable diagram, not just recovered text:
Native chart-data extraction — real OOXML numCache, not a screenshot, not OCR:
Same extraction, from DOCX — Word embeds native charts too, not just Excel; refigure reads the same cached OOXML data either way:
Composite figures — positioned, zero-loss, even when the figure itself can't be rendered (no incumbent does this — see Docling issue #1287, open >1 year):
pip install "refigure[docx,xlsx]"
refigure report.docx # markdown to stdout
from refigure.docx import convert
result = convert("report.docx") print(result.markdown) print(f"{result.charts_found} charts, {result.groups_found} composite figures")
Or without a permanent install, via uv/uvx:
uvx --from "refigure[docx,xlsx]" refigure report.docx
Optional VLM interpretation, for a composite figure the chart engine can't reconstruct on its own (see Features above):
pip install "refigure[docx,vlm]"
export OPENROUTER_API_KEY=... # or --vlm-api-key-file/--vlm-provider refigure report.docx --vlm # needs the system soffice/LibreOffice binary too
One converter, four ways to run it — pick whichever fits your pipeline. Click a heading to expand it.
CLI — a console command, stdin/stdout-first, native batch mode
refigure installs a console command — a thin wrapper over the same convert() used programmatically, no separate logic:
refigure report.docx # markdown to stdout
refigure report.docx -o report.md # markdown to a file cat report.docx | refigure --format docx # stdin, format hint required refigure reports/ -o out/ # batch: directory, walked recursively refigure a.docx b.xlsx -o out/ # batch: 2+ explicit sources
Batch mode (2+ sources, or a single directory) requires -o DIR, keeps going past a failed source by default (--fail-fast aborts on the first one instead), and always prints a summary (N/M converted, K failed) to stderr. --json emits the full result — markdown plus chart/group counts and warnings — instead of plain markdown. -v/-q control verbosity; --strict is forwarded to the same Config.strict the Python API uses.
Exit codes:
| Code | Meaning |
|---|---|
| 0 | success |
| 1 | batch mode: 1+ sources failed (keep-going default) |
| 2 | usage error (bad arguments/flags) |
| 3 | input isn't a valid document of its format |
| 4 | input isn't a valid/safe archive |
| 5 | the format's extra ([docx]/[xlsx]) isn't installed |
| 6 | unexpected internal error |
MCP server — for agents/IDEs that speak the protocol directly
refigure-mcp — the same converters as an MCP server, for agents/IDEs that speak the protocol directly instead of shelling out to a CLI or importing the library. Listed on the official MCP Registry as io.github.HelgDemidov/refigure:
pip install "refigure[mcp,docx,xlsx]"
refigure-mcp # stdio — the MCP client launches it
{
"mcpServers": { "refigure": { "command": "refigure-mcp" } } }
Or point the client at uvx instead, with no permanent install at all:
{
"mcpServers": { "refigure": { "command": "uvx", "args": ["--from", "refigure[mcp,docx,xlsx,vlm-direct]", "refigure-mcp"] } } }
refigure[full] is a shortcut for refigure[mcp,docx,xlsx,vlm-direct] — every tool, both formats, every VLM provider, one extras string.
Three tools — convert_docx, convert_xlsx, and convert_batch (multiple files in one call: one bad file reports its own error without aborting the rest) — each registered only if its format extra is actually installed. use_vlm/--vlm-provider and friends work the same as the CLI. A result too large to inline is stored and handed back as a refigure://conversion/{id} resource instead of inflating the tool response. Two prompts (ingest_for_rag, explain_conversion_warnings) help a client pick the right tool/VLM settings for the job.
Streamable HTTP is opt-in, for a shared/remote deployment — bearer-token auth is required, not optional:
echo "sk-... = alice" > tokens.txt
refigure-mcp --transport http --mcp-auth-token-file tokens.txt
Per-caller rate-limiting (protects the operator's own spend from a leaked/runaway token) applies automatically over HTTP, together with a fairness soft-cap once 2+ callers are configured; refigure-mcp --help covers every tuning flag (concurrency, timeouts, resource-store limits, batch size, VLM ceiling).
Docker — one image, CLI and MCP server both on PATH, soffice baked in
One image, both surfaces — refigure and refigure-mcp are already on PATH, no separate CLI/MCP builds to choose between. The one thing this format buys over pip/uvx that neither can: the system soffice/ LibreOffice binary the VLM composite-figure path needs is baked in, not a manual install. Multi-arch manifest (linux/amd64 + linux/arm64) — docker pull resolves the right layer automatically, including on Apple Silicon.
docker pull ghcr.io/helgdemidov/refigure:latest
Pin an exact version instead of :latest for reproducibility — e.g. :0.3.4 — see the package page for
Solo se muestra el principio; lee el resto en el repo