Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Human approval gate for AI agents: risk-scored requests that only a person can approve
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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.
APPROVAL_QUEUE_STATE_DIR, APPROVAL_QUEUE_TTL_HOURSYou 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": {
"approval-queue": {
"command": "npx",
"args": [
"-y",
"@opafex/mcp-approval-queue"
],
"env": {
"APPROVAL_QUEUE_STATE_DIR": "your-value",
"APPROVAL_QUEUE_TTL_HOURS": "your-value"
}
}
}
}Run this in your terminal
claude mcp add approval-queue --env APPROVAL_QUEUE_STATE_DIR=your-value --env APPROVAL_QUEUE_TTL_HOURS=your-value -- npx -y @opafex/mcp-approval-queueFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"approval-queue": {
"command": "npx",
"args": [
"-y",
"@opafex/mcp-approval-queue"
],
"env": {
"APPROVAL_QUEUE_STATE_DIR": "your-value",
"APPROVAL_QUEUE_TTL_HOURS": "your-value"
}
}
}
}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": {
"approval-queue": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@opafex/mcp-approval-queue"
],
"env": {
"APPROVAL_QUEUE_STATE_DIR": "your-value",
"APPROVAL_QUEUE_TTL_HOURS": "your-value"
}
}
}
}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.
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APPROVAL_QUEUE_STATE_DIR envAPPROVAL_QUEUE_TTL_HOURS envThese 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 opafex, 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 (0.2.0) reached the registry 13 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Recta
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.
Cheaper cross-chain stablecoin routes for AI agents; 5 % of the verified saving, nothing if none.
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.
A human-in-the-loop approval gate for AI agents, as an MCP server.
The agent calls request_approval before doing something risky. The action is risk-scored, and unless a rule you set covers it, you decide — in a form your MCP client shows you (MCP elicitation), or from a terminal. The agent gets a proceed: true|false it can act on.
The agent can ask; only a human can approve. There is no approve, reject or add-rule tool for the model to call. An approval gate the gated agent can open is not a gate.
Requires Node.js 20+.
Add to your client's MCP config (for Claude Code, .mcp.json in your project root):
{
"mcpServers": { "approval-queue": { "command": "npx", "args": ["-y", "@opafex/mcp-approval-queue"] } } }
Then tell the agent when to use it, for example in your project instructions:
Before deleting data, sending email, spending money or deploying, call
request_approvaland only continue ifproceedis true.
bulk_delete_users is a delete wherever the word sits — plus params.estimatedCost. The agent may pass a category, but it can only raise the score, never lower it.check_status:bash npx @opafex/mcp-approval-queue pending npx @opafex/mcp-approval-queue approve appr_3f9c1a2b4d5e --reason "checked the recipient list" npx @opafex/mcp-approval-queue reject appr_3f9c1a2b4d5e
APPROVAL_QUEUE_TTL_HOURS) and can no longer be approved.After five human approvals of the same action with no rejection, the next form suggests *always approve*. Auto-approvals do not count towards that — the system agreeing with itself is not evidence.
| Tool | Description |
|---|---|
request_approval | Submit an action (action, optional params, context, category, wait). Returns status, proceed, risk, and what to do next. |
check_status | Re-read a request by id. |
list_pending | Requests still waiting for a human, newest first. |
list_rules | The auto-approval rules a human has set (read-only). |
status is one of pending, approved, rejected, auto_approved, expired. Proceed only when proceed is true.
| URI | Contents |
|---|---|
approval://stats | Counts by status and the average time a human took to decide |
approval://rules | Current auto-approval rules |
approval://history | Last 50 decisions |
mcp-approval-queue start the MCP server (stdio)
mcp-approval-queue pending list requests waiting for a decision mcp-approval-queue show one request in full mcp-approval-queue approve [--always] [--reason ] mcp-approval-queue reject [--reason ] mcp-approval-queue rules list rules mcp-approval-queue rules add --max-risk [--description ] mcp-approval-queue rules remove mcp-approval-queue history [limit]
Patterns are globs: * matches anything, ? one character, case-insensitive. A rule can never cover high or critical risk.
| Variable | Default | Description |
|---|---|---|
APPROVAL_QUEUE_STATE_DIR | ~/.opafex/approval-queue | Where state.json (requests, rules, history) lives. The server and the CLI must point at the same directory. |
APPROVAL_QUEUE_TTL_HOURS | 24 | Hours before an undecided request expires |
State is one JSON file, written atomically under a lock file, so the server and the CLI can run at the same time.
Be clear about this before relying on it:
state.json are a human channel only if the agent cannot run the command or write the file. Coding agents such as Claude Code usually can. In that setup rely on the elicitation channel, and deny the agent the CLI and the state directory in your client's permission settings — for Claude Code, deny Bash(npx @opafex/mcp-approval-queue approve:*), Bash(npx @opafex/mcp-approval-queue rules:*), and edits under ~/.opafex/.request_approval, and has to honour proceed: false. This is a protocol for a cooperative agent and a record of what was allowed, not a sandbox. Pair it with your client's own tool permissions for anything that must be enforced.import { ApprovalQueueService, StateStore, assessRisk } from '@opafex/mcp-approval-queue';
const queue = new ApprovalQueueService(new StateStore('/var/lib/my-app/approvals')); const { request } = await queue.requestApproval({ action: 'refund_order', params: { estimatedCost: 40 } });
npm install
npm run build npm test
MIT — see LICENSE.