Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
The deterministic attack-surface perception layer for AI security agents
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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
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"zerodom": {
"command": "npx",
"args": [
"-y",
"@vexralabs/zerodom"
]
}
}
}Run this in your terminal
claude mcp add zerodom -- npx -y @vexralabs/zerodomPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"zerodom": {
"command": "npx",
"args": [
"-y",
"@vexralabs/zerodom"
]
}
}
}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": {
"zerodom": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@vexralabs/zerodom"
]
}
}
}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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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 6, 2026
The registry name was verified with the GitHub account DevHusnainAi, 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 (0.1.5) reached the registry 4 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv), Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, dotnet-mcp
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.
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ZeroDOM drives your real, logged-in browser as two identities, replays the same requests as each, and flags where one user reaches what another can't — IDOR / broken access control, caught deterministically. Open-core, runs local, no account, no API key, nothing leaves your machine.
Under the hunt is a deterministic, token-lean perception engine for AI agents — the same core powers scan , crawl and any browser-driving task. IDOR is just where it bites hardest.
[Site](https://zerodom.vexralabs.com) · [Docs](https://zerodom.vexralabs.com/docs) · [Playground](https://zerodom.vexralabs.com/playground) · [Discord](https://discord.gg/tVRznUb5Ez) · [Quickstart ↓](#quickstart)
A normal user is denied the admin console (401) — then walks in by flipping one client-controlled cookie. ZeroDOM proves it: same request, two identities, 401 vs 200 . Full recording (mp4) .
compare & sweepTwo audiences, one engine:
scan --js adds DOM-XSS sinks, the callable API surface and header posture; repeat / probe / race turn recon into verification (Repeater, mass-assignment diff, and a TOCTOU burst).aria_snapshot, with handles that resolve 1:1 and don't drift when the page re-renders.Broken access control is the #1 web vulnerability (OWASP A01) and the one automated scanners miss — because catching it means knowing *who should be allowed to do what*, not just fuzzing one session. The usual answer is a human in Burp, clicking through the app as one user, then again as another, diffing by eye.
ZeroDOM does that mechanically. Give it two logged-in sessions; it replays the same request as each and reports the deterministic tells:
200, the other 401/403 on an identical request. If the only difference between them is client-controllable (a cookie, header or param), that's broken access control.No LLM guessing, no "the AI thinks maybe." ZeroDOM surfaces the tell with the exact replay that proves it — a reviewable diff you drop straight into a bug report. You confirm the bug.
It drives your real Chrome (relay mode) over chrome.debugger, so your cookies, MFA and SSO are already done — or a throwaway browser (--stealth) if you'd rather not touch your session. Either way the page's markup never leaves your machine, and it's read-only by default: destructive actions and out-of-scope hosts are refused.
It works equally well as a one-line CLI, a recon pipeline stage, or a native tool an
AI agent drives through MCP. Same deterministic primitives, three front doors.
See it run in 10 seconds — no account, no browser download (bare zerodom is a static fetch, no Chromium needed):
pip install zerodom # or: uvx zerodom · npm i @vexralabs/zerodom
zerodom https://news.ycombinator.com # the interaction graph + a token report
That's the perception engine — a flat, 1:1-addressable graph instead of 12k tokens of HTML.
Now the flagship — find an IDOR. Save two logged-in sessions as Playwright storage_state files (one per account), then diff a protected endpoint across both:
zerodom compare https://app.example.com/api/admin/dashboard \
--as user=user.json --as admin=admin.json
{
"identities": { "user": { "status": 401, "bytes": 2616 }, "admin": { "status": 200, "bytes": 3469 } }, "only_admin": ["Manage users", "Billing & plans", "Overview"], "note": "admin authorized (200) where user denied (401) — broken access control if the only difference is client-controllable" }
That's the whole loop: same request, two identities, a 401-vs-200 split → a lead to confirm. only_admin lists the privileged controls the normal user should never see.
Don't have storage-state files? Capture one with context.storage_state(path="user.json") in Playwright, or export cookies from a logged-in session. Want the whole app, not one URL? → zerodom sweep.
compare & sweepzerodom compare — one endpoint, across identitiesFetch one URL under each saved session and diff the responses. Byte-identical content across two users on a private resource is a cross-tenant IDOR; a 401-vs-200 split is a broken boundary. only_ lists the actionable nodes each identity sees that the other doesn't.
# Sweep a range of object ids through two identities:
seq 1 500 | sed 's#^#https://app.example.com/api/invoice/#' \ | zerodom compare - --as alice=alice.json --as bob=bob.json \ | jq 'select(.identical_body_pairs | length > 0)'
zerodom sweep — the whole app, one commandcompare tests one URL. `sweep` does the entire app: it crawls as one identity to map the GET surface (pages + the API calls the JS fires), then replays every in-scope URL under *all* your identities and reports only the deterministic tells.
zerodom sweep https://app.example.com --as user=user.json --as admin=admin.json --format md
| severity | rule | url |
| -------- | ---------------------- | ------------------------------------- | | medium | access-boundary-split | https://app.example.com/api/admin/... |
Read-only throughout: only GET is replayed, destructive URLs are dropped (--deny). --format md emits a report-ready table (default is JSONL). This is the "point it at an app with two logins and it finds the broken access control" pass.
Both take --proxy (route through Burp/Caido), --header (a program's WAF-bypass token), and a scope you can lock. Challenge pages (Cloudflare / Turnstile / reCAPTCHA / hCaptcha) are detected and climbed by a scope-gated clearance ladder; a wall nothing clears is reported as an honest blocked, never worked around outside an authorized target.
repeat / probe / raceMapping an app surfaces the endpoints; these verbs act on them. repeat is a Repeater over the session (--save writes HAR/.http evidence for a report). probe replays an endpoint with a tampered body and diffs it against the baseline — an accepted, reflected field is a mass-assignment lead. race fires a concurrent burst (one body, or a mix of operations via repeated --body) to flag a check-then-act race (TOCTOU); the stdlib engine is always available, and --engine http2 multiplexes the burst over one connection via the optional zerodom[race] extra.
zerodom race https://app.example.com/api/coupon --body '{"code":"SAVE20"}' -n 30 \
--setup setup.json --check https://app.example.com/api/cart
All three are exposed to agents over MCP as zerodom_repeat / zerodom_probe / zerodom_race.
Standard MCP browser tools hand the model raw pixels (slow, stale on scroll) or an accessibility tree (no stable handles — repeated controls collide). zerodom-mcp gives your agent a flat, token-frugal graph where every click [45] resolves deterministically over CDP to exactly one element — and the same tools do cross-identity IDOR hunting the others can't. Why ↓
ZeroDOM is a native MCP server, so Claude, Cursor or any MCP agent can hunt with the same primitives. Run zerodom setup for a guided first-run (checks Chromium, prints the extension path + chrome://extensions steps, emits the config below, reports relay reachability — print-and-guide, no account, nothing leaves your machine).
// Claude Desktop: claude_desktop_config.json · Cursor: .cursor/mcp.json
{ "mcpServers": { "zerodom": { "command": "uvx", "args": ["--from", "zerodom", "zerodom-mcp"] } } }
Once before first use (so the server never downloads mid-tool-call): uvx --from zerodom playwright install chromium.
Using LangGraph, CrewAI, OpenAI Agents SDK, Pydantic AI, LlamaIndex, Google ADK or AutoGen? Ready-to-run MCP examples — same server, a few lines each — are in examples/integrations/.
The full tool set (click to expand)
| tool | what it does |
|---|---|
zerodom_parse_url(url, verbose=False, frames=False, viewport_only=False, check_occlusion=False) | navigate, return the compact graph; frames=True also reads same- and cross-origin iframes (auth portals, payment fields) |
zerodom_read_page(verbose=False) | re-read the live DOM without navigating |
zerodom_find(query) | return only the nodes matching a phrase |
zerodom_click_node(node_id) | click, then return what changed — flags a same-page no-op shortly after navigation as a possible hydration miss |
zerodom_fill_node(node_id, text) | type via real keystrokes — works in contenteditable editors (Notion, Slack, Discord, Jira) |
zerodom_hover(node_id) | hover, revealing hover-triggered menus/tooltips |
zerodom_press_key(node_id, key) | press a key on a focused node (Enter, Escape, Tab, …) |
zerodom_upload_file(node_id, path) | set a file input's value to a local path |
zerodom_drag(source_node_id, target_node_id) | drag one node onto another |
zerodom_scroll(direction, amount=800) | scroll, return what's newly visible |
zerodom_new_tab(url=None) | open a tab and make it active |
zerodom_list_tabs() | list every open tab, marking the active one |
zerodom_switch_tab(tab_id) | make another open tab active |
zerodom_close_tab(tab_id=None) | close a tab (the active one by default) |
zerodom_screenshot(path=None) | full-page screenshot of the active tab, saved to disk |
| `zerodom_set_viewport(wi
Only the beginning is shown; read the rest in the repo