Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Thermal, structural, modal, DC, and laminar-flow studies from STEP via Gmsh and Elmer.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"simulation": {
"command": "npx",
"args": [
"-y",
"simulation-mcp-server"
]
}
}
}在终端中运行这条命令
claude mcp add simulation -- npx -y simulation-mcp-server粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"simulation": {
"command": "npx",
"args": [
"-y",
"simulation-mcp-server"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"simulation": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"simulation-mcp-server"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 ottonic 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.3.0)于7天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Fomu MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Give an AI assistant first-order engineering physics on a real CAD model. This local stdio MCP server carries a STEP file through explicit meshing in Gmsh to a typed study in Elmer — steady and transient thermal, linear static structural, modal, DC conduction, and laminar flow — and returns revisioned results, with no cloud service and no prepared solver input.
Every engineering input is explicit: the materials, boundaries, and mesh are stated, never inferred, and each study, mesh, and result is revision-bound so a number can always be traced back to what produced it.
Qualified against analytic references. Gmsh 4.15.2 and Elmer (devel, most recently released as 26.2.1) complete production-SIF qualifications for every advertised physics — steady and transient thermal, static structural, modal frequency, DC potential, and steady and transient laminar flow — each against an analytic reference with mesh (or timestep) refinement.
Runs on Node 26 / TypeScript 7 against MCP SDK 2.4.0, with a Python Gmsh worker over a one-request/one-response JSON-file protocol (protocol: 1).
Distribution targets match Geometry MCP: Windows x64, macOS ARM64 (Apple Silicon), and Linux x64. Intel macOS, Linux ARM64, and Windows ARM64 are outside the target matrix. CI runs unit/artifact/process checks on these three targets, builds the pinned serial Elmer solver on each target, caches the native install, runs the analytic integration and qualification suites, then packs and smoke-tests the published tarball. This validates native execution; a standalone runtime package is not yet published.
The repository owns its artifact schema in contracts/. Builds bundle that schema and the Python worker; Gmsh and Elmer runtimes are installed separately.
From this directory:
nix develop
just setup just build export SIMULATION_INPUT_ROOTS='["/absolute/path/to/models"]' export SIMULATION_WORKSPACE=/absolute/path/to/run-workspace just start
.envrc already contains use flake; direnv allow is an alternative to nix develop. .env.example documents variables; .env is not auto-loaded. just setup installs npm dependencies without lifecycle scripts. The flake pins nixpkgs (and thus Gmsh) by commit, and pins upstream Elmer by commit. Elmer's transitive inputs use its checked-in lock.
Nix provisions the solver toolchain only on x86_64-linux. packages. .toolchain provisions Node, Gmsh, the Python wrapper and headless upstream Elmer built serially without MPI, OpenMP, ElmerIce or Lua. The analytic thermal benchmark passes with that serial solver. The dev shell also provisions Python, Ruff and Nix tooling; TypeScript language server/formatter/linter/test deps are project-local npm dependencies. Gmsh's Python module lives under its Nix package's lib, supplied through PYTHONPATH. Elmer is an external package, not compiled by npm.
Non-Nix deployments must provide compatible Gmsh Python bindings and native library plus ElmerGrid and ElmerSolver with HeatSolve, FluxSolver, SaveData and ResultOutputSolve modules. Executables are operator configuration:
| Variable | Default / meaning |
|---|---|
SIMULATION_INPUT_ROOTS | Required JSON array of existing absolute input roots |
SIMULATION_WORKSPACE | .simulation-runs; local run/artifact storage |
SIMULATION_PYTHON | python3 (Windows: python); Nix sets its wrapper |
SIMULATION_ELMERGRID | ElmerGrid |
SIMULATION_ELMERSOLVER | ElmerSolver |
SIMULATION_TIMEOUT_MS | 120000 per worker/conversion/solve; maximum 3600000 |
Generic host configuration example (environment may instead be inherited from the Nix shell):
{
"command": "node", "args": ["/absolute/path/to/simulation/dist/src/index.js"], "env": { "SIMULATION_INPUT_ROOTS": "[\"/absolute/path/to/models\"]", "SIMULATION_WORKSPACE": "/absolute/path/to/run-workspace", "SIMULATION_PYTHON": "/absolute/path/to/provisioned/simulation-python", "SIMULATION_ELMERGRID": "/absolute/path/to/ElmerGrid", "SIMULATION_ELMERSOLVER": "/absolute/path/to/ElmerSolver" } }
The public workflow is get_capabilities → inspect_model → query_model → validate_study → prepare_study → run_study → inspect_job → query_results. list_jobs recovers recent jobs after context loss and cancel_job stops an active preparation or solver process.
inspect_job accepts waitMs (up to 60 s) and then waits in-process for a terminal state instead of returning immediately, so prepare_study → inspect_job(waitMs) → run_study → inspect_job(waitMs) → query_results is normally five calls rather than dozens of polls. The state is returned whether or not the window expires. A cancelled or timed-out client request stops the mesh or the solve: ctx.signal is forwarded to the job's abort path and the record ends cancelled. Preparation and solver execution return job IDs immediately. Jobs survive client disconnects, not server shutdown. Interrupted jobs are recorded and are not resumed.
get_capabilities reports the available physics and the study shape (required and optional fields, notes, and a worked example); the machine-readable simulation://help resource carries the full study schema — per-physics material and boundary fields with units, regimes, observation quantities with time/mode selectors, enums, and a parseable example. Both are generated from one catalog so discovery cannot drift from the accepted study schema.
steady-thermal, transient-thermal, static-structural, modal, dc-conduction, and laminar-flow are implemented and benchmarked. Other physics reported by get_capabilities remain unavailable, not implied by the fact that Elmer has upstream solvers for them.
Transient studies require explicit density and heat capacity per solid, one uniform initial temperature, a positive timestep, and a step count capped at 10,000. Fixed-temperature, insulated and inward-heat-flux boundaries are supported; time-varying conditions and per-region initial temperatures are not. Transient scalar and VTU results are validated at every step. An observation may select a positive timestep-aligned time in seconds; without time, it observes the final step. Acceptance thresholds remain in the quantity's units (for example, K), not seconds.
Static structural studies require an explicit isotropic Young's modulus and Poisson ratio for every solid, and an explicit fixed-displacement, prescribed-displacement, uniform-traction, or free condition for every surface. The supported model is static, linear-elastic, and small-strain; displacement and stress summaries are unweighted nodal samples, not volume averages.
Modal studies require explicit density in addition to elastic properties, fixed-displacement/free surface assignments, and request 1–20 modes. The first modal implementation reports eigenfrequencies only; it does not expose mode shapes, damping, prestress, or harmonic response. Modal observations select a mode number and use Hz.
DC conduction studies require explicit positive isotropic electrical conductivity per solid, explicit prescribed-potential or insulated conditions on every surface, and at least two distinct prescribed potentials per disconnected conductive component. Results report the nodal potential field; current, Joule heating, magnetic effects, and transient/capacitive behavior are not modeled.
Laminar-flow studies model incompressible Newtonian fluids with explicitly assigned constant density and dynamic viscosity. Every fluid surface must be explicitly assigned either a prescribed pressure or a no-slip wall; each disconnected fluid region needs at least two distinct prescribed pressures. Steady and transient runs are supported; transient runs use first-order BDF, constant timestep, and an explicit quiescent initial velocity. The solver is Elmer's monolithic FlowSolve module; qualification covers pressure-driven square-duct flow and transient startup against the analytic rectangular-duct solution, inlet/outlet flux conservation, and mesh/timestep refinement. Flux and section averages are not exposed; reported velocity and pressure values are nodal extrema. Elmer's segregated IncompressibleNS module is installed but not qualified. Turbulence, compressibility, moving walls, nonzero initial velocity, and thermal/electric coupling are not modeled.
Selections use dimension-qualified inspection entity IDs (for example 3:1 for a volume or 2:7 for a surface), have unique names and cannot mix solids and surfaces. Every inspected entity must be assigned exactly once. Each solid selection needs one material; every surface selection defaults to insulated in thermal studies unless explicitly overridden. Structural, modal, and DC studies require explicit conditions on every surface. A thermal default is a declared engineering assumption, not an inferred boundary condition. The solver uses SI units, but study quantities may be supplied in compatible engineering units (for example mm, in, psi, ksi, lbf, degC) and are converted at the API boundary. Mesh sizes default to metres and accept mm, cm, in or ft through mesh.units. Results are SI by default; an optional displayUnits block (for example { "length": "in", "pressure": "ksi" }) returns observations in the engineer's units. Linear tetrahedra are still the only supported element type.
Material entries may carry an optional reference with the designation, source name/revision, and basis returned by a reference tool such as Standards. The study preserves this caller-supplied context alongside the explicit numeric properties; Simulation does not fetch or verify the source. A typical value remains distinct from a qualified design allowable.
Example steady thermal study after inspecting the STEP file:
{
"schemaVersion": "1", "name": "Bar conduction", "objective": "Estimate the steady temperature and heat flux", "model": { "source": { "revision": "sha256:<64 lowercase hex digits>", "uri": "file:///.../source.step", "format": "step", "units": "mm" }, "inspection": { "revision": "sha256:<64 lowercase hex digits>", "uri": "file:///.../inspection.json", "format": "json" } }, "selections": [ { "name": "bar", "entities": ["3:1"] }, { "name": "hot_end", "entities": ["2:2"] }, { "name": "cold_end", "entities": ["2:3"] }, { "name": "other_faces", "entities": ["2:4", "2:5", "2:6", "2:7"] } ], "mesh": { "minSize": 0.003, "maxSize": 0.006, "elementOrder": 1 }, "physics": { "kind": "steady-thermal", "defaultBoundary": "insulated", "materials": [ { "selection": "bar", "conductivity": { "value": 10, "units": "W/(m.K)" } } ], "sources": [], "boundaries": [ { "selection": "hot_end", "kind": "temperature", "temperature": { "value": 400, "units": "K" } }, { "selection": "cold_end", "kind": "temperature", "temperature": { "value": 300, "units": "K" } } ] }, "observations": [{ "id": "max_temperature", "quantity": "temperature_max" }], "acceptanceCriteria": [ { "observationId": "max_temperature", "operator": "<", "threshold": { "value": 410, "units": "K" } } ], "assumptions": [] }
The example entity tags are illustrative; use tags from query_model and confirm each selection against the actual part. prepare_study returns a jobId; poll inspect_job until it succeeds, then pass its prepared artifact to run_study, which returns another jobId. query_results reports solver evidence sepa
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