MCP.Market

Quirna MCP server

by quirna·io.github.quirna/mcp·v0.1.2

Ask a human before your agent acts: approval requests decided on a phone.

B82/100grade B
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Safety scan
B82/100

full report

Adoption
Growing

0 stars351 downloads/wk

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Quirna tools (2)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • check_approval
  • request_approval

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan8 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 0 days ago15/15
  • Maintainer identityregistry namespace matches repository owner7/10
Overall 82/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Quirna compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
82/100
higher than 65% of 4,460 AI and agents servers
Tools
2
the typical AI and agents server has 6
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
Downloads a week
351
more than 82% of 1,538 AI and agents servers with a package

What its tools let an agent do: 2 read

Install Quirna in Claude Code, Cursor or VS Code

Runs npx -y @quirna/mcp on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add mcp -- npx -y @quirna/mcp
Add to Cursor

What the publisher says

From the Quirna repository's README, as published. We do not edit it. Read it on GitHub

@quirna/mcp

Ask a human before your agent acts. Official Quirna server for the Model Context Protocol.

Add one block of config and your agent gains a tool it can call before doing something consequential — a refund, a production deploy, a destructive migration. A named human approves it on their phone. The agent proceeds only if they said yes, and the decision is signed and kept.

Nothing moves until someone says yes.

Your agent's framework may already have a way to pause for confirmation. This is different in three ways that matter once it is not just you at the terminal:

on their phone, behind Face ID — not to whoever happens to be watching the agent run.

  • The decision leaves the loop. It goes to whoever your policy nominates,

asked live in your organization's settings. The agent cannot choose its own approvers, and neither can a prompt injection.

  • Who approves is policy, not prompt. Quorum, risk tier and which group is

and exports to a file a third party can verify without trusting us.

  • It leaves evidence. Every decision is signed at the moment it is made,

Install

Nothing to install: the config below runs it on demand with npx. To pin it, npm install -g @quirna/mcp and use quirna-mcp as the command.

Before you start

The mobile app is in private beta. Decisions are made on the phone and

nowhere else — the Console configures policies and never decides one — so

without the app an approval request is created and then waits until it

expires. Write to hello@quirna.com and we will get you in. Everything

else below works today.

Then, in the Console:

You get a key (ck_…), shown once.

  1. A System key. Open Users → Systems and register one for this agent.

many of them are needed.

  1. A Policy, which decides who approves a given kind of request and how
  1. The app, on the phone of whoever will approve.

Configure your agent

Claude Code — claude mcp add quirna --env QUIRNAAPIKEY=ck_… -- npx -y @quirna/mcp

Cursor (~/.cursor/mcp.json), Claude Desktop (claudedesktopconfig.json) and most other clients take the same shape:

{
  "mcpServers": {
    "quirna": {
      "command": "npx",
      "args": ["-y", "@quirna/mcp"],
      "env": {
        "QUIRNA_API_KEY": "ck_your_system_key",
        "QUIRNA_REQUESTER_NAME": "Ops Agent",
        "QUIRNA_ENVIRONMENT": "production"
      }
    }
  }
}

Environment

On the key. It lives in your agent client's config file, which is often in a dotfile and sometimes in a repo. Treat it as a deployment credential: give each agent its own System rather than sharing one, scope it in the Console to the kinds it may request, and rotate it there if the file gets somewhere it should not be. A System key can only ask — it can never approve anything.

The tools

request_approval

Creates the request and waits for a human.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Quirna: common questions

Is Quirna MCP server safe?
Mostly: it is graded B (82/100). Read the Quirna safety report
How do I install Quirna?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Quirna need an API key?
Yes. The registry entry asks for QUIRNA_API_KEY.
Is Quirna maintained?
The last commit was 38 days ago (2026-09-27). The latest release is v0.1.2.
What can I use instead of Quirna?
Servers from other publishers that do the same job: Emilia Protocol MCP server, CHAP Coordinator MCP server and HOL Guard MCP server.
How does Quirna compare with other AI and agents MCP servers?
safety score 82/100 (higher than 65% of 4,460 AI and agents servers); tools 2 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Quirna

Same job from other publishers: the closest match first, then the best rated.

  • Emilia Protocol
    Exact-action approval for consequential agent actions: request, track, and verify signed receipts.
    B
  • CHAP Coordinator
    Auditable records of human decisions over AI agent work. Approvals, edits, overrides, escalations.
    A
  • HOL Guard
    Local-first AI agent security evidence and approval workflows through HOL Guard's stdio MCP server.
    A
  • Decionis
    Authorize consequential AI agent actions before execution
    A