Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Local-first evidence tracking, formal logic checks and prerequisite planning for AI agents.
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": {
"noetra": {
"command": "npx",
"args": [
"-y",
"noetra",
"mcp",
"--project",
"your-value"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add noetra -- npx -y noetra mcp --project your-valueEste necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"noetra": {
"command": "npx",
"args": [
"-y",
"noetra",
"mcp",
"--project",
"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 necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"noetra": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"noetra",
"mcp",
"--project",
"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.
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 NOETRA2, 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 (0.1.0-alpha.4) llegó al registro hace 13 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Master CSS
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.
Inspect Master CSS classes, generated CSS, and project stylesheets from your AI client.
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.
Give AI agents a checkable trail: evidence, formal logic and prerequisite plans.
Local-first, open-source MCP server · CLI · TypeScript SDK. The core runs on an ordinary CPU with Node.js; no GPU, AI subscription or model API key needed. It stores attributed evidence, checks supplied integer constraints through Z3, and plans from explicit dependencies. It does not replace your host AI.
Open the recorded preview · Try the engine locally · npm · Connect your agent · Tool API · Launch status
Developer alpha `0.1.0-alpha.4`. Check release availability for current npm, MCP Registry and hosted-demo status. Source and local tarball installation are available independently of those services. Image-to-3D is an optional, unfinished advanced workflow; no validated 90% fidelity claim exists.
With Node.js 24.11+ in 24.x, or Node.js 26+, run the published exact version:
npx --yes noetra@0.1.0-alpha.4 demo
Open http://127.0.0.1:7860. Check a claim, toggle a missing prerequisite or inspect an evidence record. These controls execute the actual engine, not canned results. Every run has a separate in-memory database, discarded afterward. No model downloads or optional 3D tools are installed. Stop with Ctrl+C.
No installation yet? The free online preview lets you inspect real recorded examples and the walkthrough. It displays stored results; it does not run the engine remotely. The command above runs the actual engine locally. The npm artifact was checked against the reviewed upload and a fresh anonymous registry installation passed the MCP/SQLite/Z3 self-test.
Watch the 60-second result walkthrough · How to reproduce the examples
The walkthrough presents actual engine outputs as labelled cards; it is not a browser recording. Capture provenance.
| Example | What NOETRA does | Scope |
|---|---|---|
Integer premise x ≥ 2, claim x ≥ 1 | Z3 checks entailment | Valid only for the supplied integer premises |
Same premise, stronger claim x ≥ 5 | Returns a counterexample | A formal counterexample, not a real-world measurement |
| Build → review → release, tests missing | Reports blocked actions | Actions/effects are supplied; nothing is published |
| One observed test result | Stores origin, digest and limitations | Remains an untrusted observation, not proof |
Maintained by NOETRA2. Core code is MIT licensed. Optional providers have their own licences and are not bundled or installed automatically. NOETRA is independent of Nexa apps and is not endorsed by Tencent, OpenAI, REA, Blender or other upstream projects.
Prerequisite: Node.js 24.11+ in the 24.x line, or Node.js 26+ and npm. No GPU is needed for the core reasoning/MCP tools.
git clone https://github.com/NOETRA2/NOETRA.git
cd NOETRA npm ci --ignore-scripts npm run build node dist/apps/cli/src/index.js help node dist/apps/cli/src/index.js doctor node dist/apps/cli/src/index.js test
GitHub's Code → Download ZIP also provides the source; extract it and run the npm commands from that folder. Once the exact release appears under the verified owner harshavardhan2 on npm, it can be run without a source build:
npx --yes noetra@0.1.0-alpha.4 test
npx --yes noetra@0.1.0-alpha.4 demo
Use a project-local installation for durable AI-host registration, rather than relying on an npm temporary cache path. Availability and publish verification are tracked in the release-status document; these commands are not a claim that an unverified package or hosted endpoint is live.
To build a local distributable:
npm pack
node dist/apps/cli/src/index.js setup --client codex --scope project
node dist/apps/cli/src/index.js setup --client cursor --scope project node dist/apps/cli/src/index.js setup --client claude --scope project
Setup previews configuration first. Cursor/Claude JSON setup requires a reviewed --apply --yes; Codex registration prints a TOML snippet for manual review. Reconnect the host afterward. No existing AI-client or REA settings are silently replaced. See installation.
| Component | Role | What it does not establish |
|---|---|---|
| Codex host agent | Interpreted the brief, authored scripts/candidates and reviewed output | Exact host model identifier was not recorded in the original experiment |
| Built-in image-generation tool | Created reference/concept artwork | Those images are not renders of a mesh; exact image-model/version was not recorded |
| Tencent Hunyuan3D-2mini Turbo | Actual learned lion geometry | Hidden surfaces, accurate anatomy, physical scale and materials remain unverified |
| TripoSR + U2Net/rembg | Optional local shape backend / foreground estimation | Not automatically fused detailed multi-view reconstruction |
| Blender 5.2.2 LTS | Mesh assembly, PBR baking, export and actual renders | A successful render is not an accuracy score |
| xatlas 0.0.11; OpenCV; NumPy/SciPy | UV charts, measured appearance, image/geometry calculations | Colour clusters do not identify anatomy or recover depth |
| Z3 | Checks explicit formal constraints | Does not judge artistic quality or physical truth |
| REA 6.7.0 / optional Ghidra | Authorized software investigation | They are analysis tools, not image-to-3D generators |
The lion model revision is f90a0f7df7d5e6f71109cf333f6a95a0ae3194a6; the upstream source commit is f8db63096c8282cb27354314d896feba5ba6ff8a. The pinned manifest includes full checkpoint/source hashes. Model weights, third-party applications, private accounts and local model caches are excluded.
Hunyuan is a separately licensed optional provider, not MIT-licensed model weights. Review its licence, notice and model/source provenance before provisioning it. Its licence contains territory and use restrictions. Powered by Tencent Hunyuan when that provider is enabled; Tencent does not sponsor, endorse or operate this independent project.
The images below are Blender renders of actual meshes, not generated concept pictures presented as 3D output. Details, settings and limitations are in comparisons.
Left: without NOETRA, a new host-authored procedural lion built directly in Blender from primitives, remeshing and solid geometry. No NOETRA code or learned shape model generated that mesh. Right: with NOETRA, the existing lion created through its Hunyuan3D-2mini Turbo workflow. Both pictures render real meshes using the same clay material, lighting, view directions and normalized height. The procedural lion is stylized; these different methods are not a controlled test of NOETRA's quality or accuracy. The downloadable mesh, script and second angle are in comparisons.
We also ran a separate direct Hunyuan inference with NOETRA bypassed and otherwise matching inputs/settings. That result is identical to the workflow's raw mesh; the report preserves this evidence. No numerical accuracy gain is claimed.
The local core TypeScript/build checks, 71 Node tests and CLI protocol self-test passed. The reconstruction Python suite and focused cache/region tests passed (156 tests across the recorded runs). The example meshes were actually exported, reimported and rendered. GitHub Actions results, once available, are separate from these local checks.
The lion mesh and painting remain partial. Accurate facial anatomy, semantic part-to-mesh correspondence, calibrated detailed multi-view fusion, intrinsic albedo/PBR recovery and reliable unseen geometry are unfinished. The automatic appearance-readiness gate remains false; an explicitly requested unverified paint preview does not override it or replace the accepted model.
Accuracy is not measured by triangle count, watertightness, successful export or a visually pleasing screenshot. We need a defined metric, independent ground-truth 3D data, held-out inputs and reproducible evaluation before making a numerical fidelity claim such as 90%.
Architecture · Tool API · Security · REA · Reconstruction · Appearance analysis · Surface painting · Third-party notices
npm ci --ignore-scripts
npm run check
Python reconstruction tests require separately provisioned local dependencies; model inference is optional and is not run merely by installing the core package. Report reproducible problems through GitHub Issues, with sanitized inputs and logs. Do not upload credentials, private images, AI-client settings or model weights.