Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Runs physverify checks on physics code. It runs the code it checks: use on trusted code only.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"physverify": {
"command": "uvx",
"args": [
"physverify",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add physverify -- uvx physverify mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"physverify": {
"command": "uvx",
"args": [
"physverify",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"physverify": {
"type": "stdio",
"command": "uvx",
"args": [
"physverify",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account rcgiri-physics, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.5.1) reached the registry 12 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Fomu MCP
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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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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Checks that a simulation solves the equations it claims, at the order of accuracy it claims, not just that it runs.
physverify is actively evolving (v0.7.0), welcoming contributions and test cases from the computational physics community. Status: under active development and maintenance, tested on a growing corpus of public physics codes; releases come at milestones. Scope: numerical solutions of ODEs and PDEs (time integration, convergence, conservation), plus a few Monte Carlo checks. It needs only NumPy.
pip install physverify
physverify demo
The demo checks a correct solver (all checks pass), then the same solver with the damping 10% too large (all fail):
New to this? Start here walks through installation and a first check in about ten minutes, with a prompt to paste if you use an AI coding assistant.
physverify scan PATH reads the code (it runs nothing) and flags Runge-Kutta methods that do not have their stated order (written as tables, as class attributes or as stages in code), grid spacings that do not match their grid, near-miss physical constants, and inverse function pairs worth a round-trip test.physverify init verify_solver.py --solver mysolver --order 4 writes a spec; fill in the equations (from the physics, not from your code) and run physverify run verify_solver.py.check_tableau(A, b, c, claimed=3) from physverify.butcher checks its order, stage order and stability from the coefficients alone.check_order(hs, errors, expected=2) gives PASS, FAIL or INCONCLUSIVE with a reason.A failed check fails the job, like a broken unit test (CI guide: options, pre-commit, pytest):
- uses: rcgiri-physics/physverify@v0.7.0
with: specs: tests/verify_*.py
Getting started · Recipes · What a PASS means · Troubleshooting · API
Of 37 bugs seeded into five small solvers, it flagged 35 (plain "compare with one answer" tests: 27), with no false alarms. The bugs and checks were written by the same person, so this shows the tool works as designed, not how it does on other people's code. On public physics repositories, 74 defects were reported to authors; 14 of them were found by a physverify check as such, 11 by simply running the code, and the rest by the per-repository test scripts or by reading the code. physverify scan alone, with no script, now finds 18 of the 74, up from 2 in its first version, and found 7 new defects in the same repositories (which found what). The counts describe that sample only and are not a bug rate. Details: results, and results/README.md to regenerate every table.
Works best for ODEs; PDEs only in 1D so far. Your code needs a way to add a source term, or a small wrapper that can itself be wrong. A PASS means these checks found nothing wrong; it does not prove the simulation correct, and it is only as independent as the reference you wrote: see What a PASS means.
Help is welcome: a trial report on your own solver, seeded bugs written by someone other than the author, adapters, documentation. See CONTRIBUTING.md, the code of conduct, SUPPORT.md for help, SECURITY.md on running untrusted code, and AGENTS.md for AI assistants. To cite, use doi:10.5281/zenodo.23534512 or CITATION.cff. Changes: CHANGELOG.md; plans: ROADMAP.md. The methods are standard and other tools do parts of this, some better (NodePy for Runge-Kutta analysis); see related work and credits. MIT licence, copyright (c) 2026 Ram Chandra Giri.