Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Testing MCP for coding agents: exercise real user journeys, find bugs, verify them with evidence.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"argus": {
"command": "uvx",
"args": [
"argus-testing"
]
}
}
}Run this in your terminal
claude mcp add argus -- uvx argus-testingPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"argus": {
"command": "uvx",
"args": [
"argus-testing"
]
}
}
}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": {
"argus": {
"type": "stdio",
"command": "uvx",
"args": [
"argus-testing"
]
}
}
}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.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
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 7, 2026
The registry name was verified with the GitHub account chriswu727, 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
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
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 (0.12.1) reached the registry yesterday.
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, SuperCollider
Servers in the same category from other makers, sorted by stars.
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.
Make sound with SuperCollider: synths, drums, chords, melodies and soundscapes over OSC.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Quick start · What you get · Engineering · Documentation · Product page
Argus is an MCP testing server for Claude Code, Codex, Cursor and other coding agents. It gives your existing agent browser tools to exercise your app, check suspected bugs and produce reports with evidence. The agent decides what to test; Argus handles browser actions, repeatable checks and the results.
Test my web app at http://localhost:3000 and look for bugs.
Your agent can explore user flows, inspect what changed after each action and recheck suspected failures on a fresh page load. You can also give it specific goals, such as testing account settings or checking whether saved data survives a refresh.
For example, a task may disappear after deletion but return after a refresh. Argus can check that behavior on fresh loads, retain the evidence and export a test for the persistence failure. The receipt confirms that symptom; it does not identify the root cause or fix the application.
Reports are available as HTML, JSON, JUnit and SARIF. Test exports currently support findings verified through fresh-load text checks. Uploads, restored browser state and other unsupported steps require manual translation.
Requires Python 3.11+, Chromium and an MCP-capable coding agent. With uv:
uvx --from argus-testing python -m playwright install chromium
uvx --from argus-testing argus-mcp --doctor
Connect it to Claude Code:
claude mcp add argus -- uvx --from argus-testing argus-mcp
Or Codex:
codex mcp add argus -- uvx --from argus-testing argus-mcp
Then ask your agent to test your app. Use test accounts and data you can change: replaying a journey can repeat its writes.
Cursor, other MCP clients and troubleshooting · Claude plugin · Codex plugin
0.12.1: generated tests keep application values in private parameters and stop before execution when steps or configuration are incomplete. Upgrade from 0.12.0 for these protections. See the releases and changelog.
Where to start reading the code:
Argus is still an alpha project. A fresh load normally retains authentication and browser storage; it is not a reset of the backend. A reproduced symptom is not proof of complete coverage or of a requirements violation. Generated tests and screenshots should be reviewed before sharing, especially with sensitive application data. Privacy details.
The deterministic fixtures cover 34 seeded scenarios. That measures what the tools can exercise with scripted steps, not an agent's bug-discovery rate. In a small paired Codex evaluation, both Argus and the browser baseline found all 5 predeclared defects. Argus also found one fixture defect identified after the run and used more time and tokens. These results do not establish general superiority.
The evaluation guide documents the method, limits and reproduction commands. Browser and unit tests run locally without model calls; model-based evaluations are separate and opt-in.
Built by Yichen Wu · yichenwu.dev