Deterministic fact-verification layer for AI agents — verify IBANs, VAT, crypto addresses, domains, IDs & more against checksums and curated data, not guesses.
git clone https://github.com/qinisolabs/qiniso{
"mcpServers": {
"qiniso": {
"command": "node",
"args": ["/path/to/qiniso/dist/index.js"]
}
}
}MCP Servers overview
<div align="center">
<img src="docs/logo.svg" width="96" height="96" alt="Qiniso" />
# Qiniso
**The deterministic fact-verification layer for AI agents.**
*Verified, trustworthy data tools for AI agents. "Qiniso" means "truth" in Zulu.*
[Website](https://qinisolabs.github.io/qiniso/) · [MCP endpoint](https://qiniso.qinisolabs.workers.dev/mcp) · [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers?search=qiniso)
</div>
---
Agents confidently emit IBANs, phone numbers, domains, VAT numbers and crypto addresses that are subtly — and silently — **wrong**. Qiniso checks the structured facts an agent produces against **checksums and curated authoritative data**, so a bad value is caught instead of trusted.
It's the deterministic complement to the guardrail stack: security guardrails check whether output is *safe*, structure guardrails check it's *well-formed*, and hallucination guardrails ask another LLM if it's *faithful to the prompt*. **None of them check whether a structured fact is actually correct against the real world** — because that needs computation or curated data, not another model's opinion. That's Qiniso.
> On arbitrary identifiers, a frontier LLM validates them **wrong ~91% of the time, cold and silently. Qiniso: 0%.**
## Add it to Claude
Settings → Connectors → **Add custom connector**, and paste — no login, no key:
```
https://qiniso.qinisolabs.workers.dev/mcp
```
Stateless, reads no user data, requires no secrets.
## Use it as a library
Every check is also a typed function — no MCP required:
```bash
npm i @qinisolabs/qiniso
```
```ts
import { validateIban, validateVat } from "@qinisolabs/qiniso";
validateIban("GB82 WEST 1234 5698 7654 32");
// { valid: true, country: "United Kingdom", ... }
```
## What it verifies — 33 tools across 8 domains
| Domain | Tools |
| --- | --- |
| **Identifiers** | IBAN, payment card (Luhn + brand), ISBN-13, VIN |
| **Web / network** | TLD & domain (IANA root zone), IP, UUID, URL, email |
| **Finance** | ISIN, CUSIP, SEDOL, LEI, US ABA routing |
| **Crypto** | Ethereum (EIP-55), Bitcoin (Base58Check / Bech32) addresses |
| **National & tax IDs** | Brazil CPF/CNPJ, South Africa ID, Spain DNI/NIE, India Aadhaar, EU/UK VAT |
| **Academic** | ISBN-10, ISSN, ORCID |
| **Locale** | Phone (global), date parsing, currency, holidays (~200 countries), UK VAT-by-date |
| **Addresses** | UK/US address parsing |
Each tool wraps an authoritative method — a published checksum standard, an audited library (libphonenumber-js, jsvat, date-holidays, @noble/hashes), or curated reference data (the IANA root zone, UK VAT history).
## What it is *not*
- **Not a live-data provider.** It verifies facts you give it; it does not return the current time, weather, or live exchange rates.
- **Not a credential sink.** It never asks for secrets or API keys. (For JWT signature verification, use a library in your own runtime so the secret never leaves your machine.)
- **Not a registration check.** It validates a VAT number's checksum, not whether it is live-registered (VIES); it confirms a domain's TLD is real, not that the domain is registered.
## Architecture
A TypeScript monorepo. Each domain is a typed library in `packages/*`; the `qiniso` umbrella aggregates them and exposes one MCP server over three transports — **stdio** (local / `npx`), **Streamable HTTP** (self-host), and a **Cloudflare Worker** (the hosted edge endpoint). The same core powers the importable library.
```bash
npm install
npm run build
npm test
```
## License
Apache-2.0
What people ask about qiniso
What is qinisolabs/qiniso?
+
qinisolabs/qiniso is mcp servers for the Claude AI ecosystem. Deterministic fact-verification layer for AI agents — verify IBANs, VAT, crypto addresses, domains, IDs & more against checksums and curated data, not guesses. It has 0 GitHub stars and was last updated today.
How do I install qiniso?
+
You can install qiniso by cloning the repository (https://github.com/qinisolabs/qiniso) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is qinisolabs/qiniso safe to use?
+
qinisolabs/qiniso has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.
Who maintains qinisolabs/qiniso?
+
qinisolabs/qiniso is maintained by qinisolabs. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to qiniso?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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