Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Agent toolchain for the DualSPHysics SPH solver: case creation, runs, post-processing, validation.
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.
DSPH_GENCASE, DSPH_SOLVER, DSPH_PARTVTK, DSPH_MEASURETOOL, DSPH_JOBS_DIR, DSPH_OMP_THREADSNecesitas
¿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": {
"dualsphysics": {
"command": "uvx",
"args": [
"dualsphysics-mcp"
],
"env": {
"DSPH_GENCASE": "your-value",
"DSPH_SOLVER": "your-value",
"DSPH_PARTVTK": "your-value",
"DSPH_MEASURETOOL": "your-value",
"DSPH_JOBS_DIR": "your-value",
"DSPH_OMP_THREADS": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add dualsphysics --env DSPH_GENCASE=your-value --env DSPH_SOLVER=your-value --env DSPH_PARTVTK=your-value --env DSPH_MEASURETOOL=your-value --env DSPH_JOBS_DIR=your-value --env DSPH_OMP_THREADS=your-value -- uvx dualsphysics-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"dualsphysics": {
"command": "uvx",
"args": [
"dualsphysics-mcp"
],
"env": {
"DSPH_GENCASE": "your-value",
"DSPH_SOLVER": "your-value",
"DSPH_PARTVTK": "your-value",
"DSPH_MEASURETOOL": "your-value",
"DSPH_JOBS_DIR": "your-value",
"DSPH_OMP_THREADS": "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.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"dualsphysics": {
"type": "stdio",
"command": "uvx",
"args": [
"dualsphysics-mcp"
],
"env": {
"DSPH_GENCASE": "your-value",
"DSPH_SOLVER": "your-value",
"DSPH_PARTVTK": "your-value",
"DSPH_MEASURETOOL": "your-value",
"DSPH_JOBS_DIR": "your-value",
"DSPH_OMP_THREADS": "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.
DSPH_GENCASE envDSPH_SOLVER envDSPH_PARTVTK envDSPH_MEASURETOOL envDSPH_JOBS_DIR envDSPH_OMP_THREADS envEsta 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 vegetableno1, 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 (0.2.0) llegó al registro hace 43 días.
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, Tools 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.
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Design, run, and verify DualSPHysics simulations from an AI agent — not just stare at them.
Ten Model Context Protocol tools wrap a local DualSPHysics SPH toolchain end to end: design cases as structured parameters (no hand-written XML, no solver needed to iterate), run them as background CPU jobs with progress, throughput and the solver's own ETA on tap, post-process into ParaView-ready VTK and CSV time series, and verify a 2D dam-break against the Koshizuka & Oka (1996) experiment with per-time errors and MAE / RMSE / max.
The server only launches the DualSPHysics command-line tools as subprocesses; DualSPHysics itself is not distributed here — it is free LGPL-2.1-or-later software, this package neither links nor redistributes its code or binaries, so the MIT licence carries no extra obligations. If you publish work using DualSPHysics, cite *Dominguez et al. (2022), Computational Particle Mechanics 9:867–895, doi:10.1007/s40571-021-00404-2.*
| Tool | What it does |
|---|---|
check_environment | Find the four DualSPHysics tools on this machine: resolved path, provenance (env var, PATH, scan), version, solver feature flags; install hints when one is missing. |
create_case | Describe a 2D dam-break experiment in plain parameters and get a GenCase *_Def.xml back — no XML by hand, no solver needed. Returns a particle-count estimate for self-checking. |
edit_case | Change parameters of an existing case (in place or to a save_path), re-validating the merged result. |
describe_case | Read a case file back as a summary: dp, domain, column/tank/obstacle, timing, gauges, particle estimate. |
gencase | Discretise the case into Case.xml + Case.bi4 (plus preview VTK) and report the real particle counts. |
run_case | Start the CPU solver in the background (jobs/ directory, Run.out, Part_*.bi4) and return a job_id immediately. |
job_status | Poll a job: state, t/tmax, percent, the solver's Time/Sec throughput and projected finish, Run.out tail. |
partvtk | Turn Part_*.bi4 output into VTK particle files for ParaView; filters and variables pass through. |
measure_tool | Probe the solution at points and get CSV time series back (comma separator enforced for deterministic parsing). |
validate_dambreak | Reconstruct the dam-tip surge front from the CSV and score it against the embedded Koshizuka & Oka (1996) series: per-time errors + MAE/RMSE/max. |
Working chain: check_environment → create_case → describe_case → gencase → run_case → poll job_status → partvtk + measure_tool → validate_dambreak. Vocabulary, three guards and particle-estimate arithmetic: docs/case-generation.md.
Behaviours of the wrapped tools that their -h output does not tell you:
create_case containment-checks every domain.measure_tool forces commas unless the caller passes their own -csvsep.# comment lines; MeasureTool errors print on stdout, not stderr.Time/Sec in Run.out is wall-clock seconds per simulated second — not steps/second; the row tail is the solver's projected finish.Run.out row formats differ between solver v5.0/v5.2 and v5.4; the parser handles both.All fourteen contracts (formats, exit codes): docs/domain-contracts.md.
Python 3.10+. The binaries are discovered from DSPH_* environment variables, PATH, or conventional install roots (/opt, /usr/local, ~/softwares, ~, cwd → /DualSPHysics*/bin/linux).
uv sync # or: python -m venv .venv && .venv/bin/pip install -e .
Getting the solver (the GitHub repository ships GenCase / PartVTK / MeasureTool prebuilt but not the solver):
git clone https://github.com/DualSPHysics/DualSPHysics and build the CPU solver with make -f Makefile_cpu (g++ only, no CUDA needed), then copy the prebuilt tools from bin/linux/.Configure through environment variables (no .env parsing; see .env.example — the same paths appear in examples/mcp_config.example.json):
DSPH_GENCASE=/home/<user>/softwares/DualSPHysics/bin/linux/GenCase_linux64
DSPH_SOLVER=/home/ /softwares/DualSPHysics/bin/linux/DualSPHysics5.4CPU_linux64 DSPH_PARTVTK=/home/ /softwares/DualSPHysics/bin/linux/PartVTK_linux64 DSPH_MEASURETOOL=/home/ /softwares/DualSPHysics/bin/linux/MeasureTool_linux64 DSPH_JOBS_DIR=/abs/path/to/jobs # optional, default ./jobs DSPH_OMP_THREADS=8 # optional, default all cores
.venv/bin/python mcp_server.py # hub-style entry point (stdio)
.venv/bin/dualsphysics-mcp # console script uvx dualsphysics-mcp # published on PyPI
Client registration templates: examples/mcp_config.example.json:
{ "mcpServers": { "dualsphysics-mcp": { "command": "uvx", "args": ["dualsphysics-mcp"] } } }
claude mcp add dualsphysics-mcp -- /abs/repo/path/.venv/bin/python /abs/repo/path/mcp_server.py
examples/dambreak_val2d/ holds the showcase: the official validation layout (dp = 0.01 m; 1 m × 2 m water column in a 4 m × 3 m tank; TimeMax = 2 s, TimeOut = 0.01 s; Verlet / Wendland / artificial viscosity 0.02 / Fourtakas DDT 0.1), regenerated by gen_dambreak_val2d.py (MIT), a surge-front MeasureTool points file (401 points along z = 0.03 m), and the digitised experiment.
Measured on this case (GenCase v5.4.354 / solver v5.4.355, 8 CPU threads, i5-10210U):
| Quantity | Value |
|---|---|
| Total particles | 21,001 (fluid 20,000 + bound 1,001) |
| Part files | 201 (Part_0000 … Part_0200) |
| Solver wall time (TimeMax = 2 s) | ≈ 14 min |
| Dam-tip MAE vs experiment (0.09–0.75 s) | 0.220 m (22.0 % of the column); RMSE 0.240 m |
| Dam-tip error, early collapse (t ≤ 0.2 s) | within ±0.01–0.16 m |
| Wall impact | front pins at 3.98 m at t ≈ 0.67 s |
The residual is SPH physics, not a measurement artefact: the front extraction tracks the solver's own SWL gauge (mean deviation 8 mm < 10 mm point spacing), and the experiment ends at X/a ≈ 4.13 — beyond the 4 m tank — so the comparison saturates after wall impact (validate_dambreak notes impact_time_s).
Agent transcript:
check_environment() # all four tools found
gencase("examples/dambreak_val2d/CaseDambreakVal2D_Def.xml") -> particle_counts: total=21001 fluid=20000 bound=1001 run_case(" /CaseDambreakVal2D") # returns job_id job_status(job_id) # poll until percent=100 partvtk(job_id=job_id) # 201 fluid VTK files measure_tool(job_id=job_id, points_file="examples/dambreak_val2d/points_damtip.txt") validate_dambreak(csv_path=" ", points_file="examples/dambreak_val2d/points_damtip.txt")
validate_dambreak reports per-time errors plus MAE / RMSE / max in metres and as % of the 1 m column. The figure comes from examples/make_validation_figure.py; examples/render_dambreak.py turns the same run's Part_*.vtk into an MP4 animation (dev dependencies).
uv run pytest -q # or: .venv/bin/python -m pytest
uv run ruff check .
The suite is green without any solver installed (discovery, command construction, log-fixture parsing, validation math, case generation, stdio end-to-end). Tests marked solver exercise a real local toolchain and auto-skip otherwise.
src/dualsphysics_mcp/ — MCP server, tool discovery and config, error codes, the ten tools in tools/.examples/ — validation case, create_case_demo.py, figure + animation scripts, client template.tests/ — pytest suite (solver tests auto-skip)..env, job outputs and generated results.examples/dambreak_val2d/ are digitised facts cited to Koshizuka & Oka (1996) as shipped with the DualSPHysics examples; the generated case XML and all code here are original MIT content — details in CONTRIBUTING.md.