Official description7 sourcesMCP servers8d ago
qinisolabs/qiniso
Verify IBAN, VAT, VIN, barcodes, national an
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Config template (adjust for your client)
claude mcp add qiniso -- npx -y qiniso
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
- Star count
- 1 ★ · qinisolabs/qiniso · read from the GitHub search API · (checked 2026-10-16 20:00:20)
- Source
- collected from the punkpeye/awesome-mcp-servers list · type: MCP server
- Harvest history
- first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
- Score
- score 703 · 1 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
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repository
qinisolabs/qiniso；first catalogued 2026-10-09；last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.Third-party quality signals
Qiniso
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
**The deterministic fact-verification layer for AI agents.**
*Verified, trustworthy data tools for AI agents. "Qiniso" means "truth" in Zulu.*
Website · npm · MCP endpoint · MCP Registry
---
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:
Stateless, reads no user data, requires no secrets.
Use it as a library
Every check is also a typed function — no MCP required:
What it verifies — 56 tools across 8 domains
| Domain | Tools |
| --- | --- |
| **Identifiers** | IBAN, payment card (Luhn + brand), ISBN-13, VIN, GTIN/UPC/EAN barcodes (+ GS1 country) |
| **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, Italy, Poland, Netherlands, Belgium, Nordics, Portugal, Turkey, China, Germany Steuer-IdNr, France NIR, Switzerland AHV, Mexico CURP, Croatia OIB, Romania CNP, Bulgaria EGN, Estonia, Czech/Slovak rodné číslo, 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.
*Verified, trustworthy data tools for AI agents. "Qiniso" means "truth" in Zulu.*
Website · npm · MCP endpoint · MCP Registry
---
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:
Stateless, reads no user data, requires no secrets.
Use it as a library
Every check is also a typed function — no MCP required:
What it verifies — 56 tools across 8 domains
| Domain | Tools |
| --- | --- |
| **Identifiers** | IBAN, payment card (Luhn + brand), ISBN-13, VIN, GTIN/UPC/EAN barcodes (+ GS1 country) |
| **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, Italy, Poland, Netherlands, Belgium, Nordics, Portugal, Turkey, China, Germany Steuer-IdNr, France NIR, Switzerland AHV, Mexico CURP, Croatia OIB, Romania CNP, Bulgaria EGN, Estonia, Czech/Slovak rodné číslo, 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.
- Source
- awesome · https://github.com/qinisolabs/qiniso
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