Open-source B2B and marketplace ecommerce; new stores include an MCP server for AI agents.
Otr Protocol
Overview
Description from the maker (original English)
Merchant trust verification for AI agents. One call = trust score, badge, and purchase safety.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Online shops & payments
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- npmNode.js installed (for the npx command)
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": {
"otr-protocol": {
"command": "npx",
"args": [
"-y",
"@otr-protocol/mcp-server"
]
}
}
}Run this in your terminal
claude mcp add otr-protocol -- npx -y @otr-protocol/mcp-serverOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"otr-protocol": {
"command": "npx",
"args": [
"-y",
"@otr-protocol/mcp-server"
]
}
}
}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.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"otr-protocol": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@otr-protocol/mcp-server"
]
}
}
}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.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
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
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account yb48666-ctrl, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Online shops & paymentsi
- More stars than 0% of the other 1743 servers in this category
- Published to the registry more recently than 2% of the other 1743 servers in this category
- Basic checks equal to or better than 100% of the other 1743 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Otr Protocol safe?
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.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
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).
Is it still maintained?
The GitHub repo last changed –, and the latest version (3.1.0) reached the registry 8 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
What can I use instead?
In the same category: Spree Commerce: open-source B2B and marketplace ecommerce, Stripe MCP, MCP Cn Commerce
Alternatives
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
Stripe MCP
Stripe’s official server lets AI view and manage customers, products, payments and invoices. Connect to Stripe’s cloud and sign in with OAuth.
MCP Cn Commerce
8 read-only MCP platform entries; support is operation-specific; merchant live acceptance pending
README from the maker
Open the README
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.
OTR Protocol
The merchant trust layer for AI agent commerce
Deterministic, verifiable, open-source merchant trust scoring for the agentic economy
Protocol v4.1
Specification • Scoring Algorithm • Quick Start • Packages • Contributing
The Problem
AI agents are increasingly making purchase decisions on behalf of consumers. The agentic commerce stack is taking shape -- but there is a critical missing layer:
┌──────────────────────────────────────────────────────────────────┐
│ AI Agent Commerce Protocol Stack │ ├──────────────────────────────────────────────────────────────────┤ │ │ │ Visa TAP ·············· Agent Identity Verification │ │ Google UCP ············ Structured Data Exchange │ │ Stripe ACP ············ Payment Processing │ │ │ │ ┌───────────────────────────────────────────────────────────┐ │ │ │ OTR Protocol ····· MERCHANT TRUST VERIFICATION ◀━━━━━ │ │ │ │ "Is this merchant safe to buy from?" │ │ │ └───────────────────────────────────────────────────────────┘ │ │ │ │ Visa TAP answers "Who is the AI agent?" │ │ Google UCP answers "What products are available?" │ │ Stripe ACP answers "How do I pay?" │ │ OTR answers "Should I trust this merchant?" ◀━━ ONLY OTR │ │ │ └──────────────────────────────────────────────────────────────────┘
Without OTR, AI agents operate blind -- unable to distinguish a legitimate retailer from a sophisticated scam site. This exposes consumers to fraud and erodes trust in the entire agentic commerce ecosystem.
The Solution
OTR (Open Trust Registry) provides deterministic, verifiable merchant trust scores using 6 verification dimensions, a 10-layer anti-fraud pipeline (Layer 0: Google Web Risk one-vote veto + Layers 1-9: core detection engine), and three-layer immutable audit trail. It is fully open-source (MIT), machine-readable, and designed from the ground up for AI agent consumption.
Key Properties
- Deterministic -- Same inputs always produce identical outputs. Any validator can reproduce any score.
- Verifiable -- All data sources are publicly accessible. No hidden factors or proprietary signals.
- Unforgeable -- Verification dimension weighted at 40% in public assessment. SEC filings, Wikidata entries, and 10-year domain age cannot be faked.
- Tamper-proof -- SHA-256 hash chain + Base L2 blockchain anchoring + IPFS monthly snapshots.
- Fair -- No pay-for-trust. Scores reflect behavior, not subscription level.
- Category-aware -- Three site categories (ecommerce / saas / non_commerce) with tailored scoring weights.
- Safety-first -- Google Web Risk Layer 0 one-vote veto: flagged domains get score=0, status SUSPENDED.
Quick Start
# Verify any merchant instantly
npx @otr-protocol/validator verify nike.com
Output:
┌──────────────────────────────────────────────┐
│ nike.com GOLD │
│ Trust Score: 88/100 Category: ecommerce │
│ OTR-ID: OTR-1C-7F3A2B9E4D1C-K4 │
│ │
│ Verification: 85 ██████████████░░ │
│ Security: 80 █████████████░░░ │
│ Governance: 72 ████████████░░░░ │
│ Transparency: 75 ████████████░░░░ │
│ Data Quality: 65 ██████████░░░░░░ │
│ Fulfillment: -- (COLD mode) │
└──────────────────────────────────────────────┘
For AI Agents (MCP Server)
The OTR MCP Server uses the standard Model Context Protocol and works with all MCP-compatible clients.
Claude Desktop / Claude Code -- add to claude_desktop_config.json:
{
"mcpServers": { "otr": { "command": "npx", "args": ["@otr-protocol/mcp-server"] } } }
Cursor / Windsurf / Cline -- same configuration in .cursor/mcp.json or equivalent. Any client implementing the MCP specification works out of the box.
Now any AI agent can verify merchants in natural language:
*"Is nike.com trustworthy?"* --> OTR returns trust score 88/100, badge GOLD, and a 6-dimension breakdown (Verification, Security, Governance, Transparency, DataQuality, Fulfillment) with evidence sources.
Two MCP Tools — One Call = Complete Answer
| Tool | Description | Returns |
|---|---|---|
verify_merchant | Complete merchant profile in one call | Trust score (0-100), badge, 6-dimension breakdown, safety status (Google Web Risk), site classification (ecommerce/saas/non_commerce), entity data, policy URLs, data sources |
search_registry | Search the OTR merchant registry | Paginated merchant list with scores, badges, and recommendations |
Design philosophy: AI agents should get everything they need in a single tool call. verify_merchant returns trust assessment + purchase capabilities + links + policy URLs + data freshness — no need to chain multiple calls.
TypeScript SDK
import { OtrClient } from "@otr-protocol/sdk";
const otr = new OtrClient(); const result = await otr.verify("nike.com");
console.log(result.trustScore); // 88 console.log(result.badge); // "GOLD" console.log(result.dimensions); // { verification: 85, security: 80, ... }
// Search the registry const results = await otr.search("electronics", { minScore: 70 });
Core Scoring Engine
import { calculateTrustScore } from "@otr-protocol/core";
// Deterministic: same inputs always produce identical outputs const result = calculateTrustScore({ hasSecFiling: true, hasStockSymbol: true, stockExchange: "NYSE", hasWikidataId: true, trancoRank: 500, domainAgeYears: 15, // ... 40+ evidence fields });
console.log(result.trustScore); // 88 console.log(result.badge); // "GOLD" console.log(result.tier); // "TIER_4"
Architecture
┌─────────────────────────────────┐
│ AI Agent / Application │ │ "Should I buy from example.com?" │ └──────────────┬──────────────────┘ │ ┌───────────────────┼───────────────────┐ │ │ │ ┌─────▼─────┐ ┌──────▼──────┐ ┌──────▼──────┐ │ MCP Server │ │ REST API │ │ SDK │ │ (stdio) │ │ /api/otr │ │ npm pkg │ └─────┬──────┘ └──────┬──────┘ └──────┬──────┘ │ │ │ └───────────────────┼───────────────────┘ │ ┌──────────────▼──────────────┐ │ OTR Scoring Engine │ │ @otr-protocol/core │ │ │ │ ┌─────────────────────────┐ │ │ │ 6 Dimension Evaluators │ │ │ │ Verification | Security │ │ │ │ Governance | Transparency│ │ │ │ DataQuality | Fulfillment│ │ │ └─────────────────────────┘ │ │ ┌─────────────────────────┐ │ │ │ 10-Layer Anti-Fraud │ │ │ │ Domain Age | SSL | DNS │ │ │ │ Pattern | Tranco | ... │ │ │ └─────────────────────────┘ │ │ ┌─────────────────────────┐ │ │ │ Brand Fast-Track │ │ │ │ SEC + Tranco + Wikidata │ │ │ └─────────────────────────┘ │ └──────────────┬──────────────┘ │ ┌─────────────────────────┼─────────────────────────┐ │ │ │ ┌────────▼────────┐ ┌──────────▼──────────┐ ┌─────────▼─────────┐ │ Public Data │ │ Merchant Bridge │ │ Immutable Audit │ │ Sources │ │ (Verified Only) │ │ Trail │ │ │ │ │ │ │ │ SEC EDGAR │ │ Product Catalog │ │ SHA-256 Hash │ │ Wikidata │ │ Order Data (agg) │ │ Chain │ │ Tranco List │ │ Delivery Metrics │ │ Base L2 Anchoring │ │ DNS Records │ │ Tracking Numbers │ │ IPFS Snapshots │ │ SSL Certs │ │ (desensitized) │ │ │ │ Finnhub.io │ │ │ │ │ │ Google Web Risk │ │ │ │ │ │ Website Scan │ │ │ │ │ └─────────────────┘ └──────────────────────┘ └───────────────────┘
How Scoring Works
6 Trust Dimensions
Weights vary by site category:
| # | Dimension | E-Commerce COLD | SaaS COLD | AUTH Mode | What It Measures |
|---|---|---|---|---|---|
| 1 | Verification | 0.40 | 0.37 | 0.10 | Stock exchange, Wikidata, GLEIF LEI, domain age, Tranco rank, payment processors |
| 2 | Security | 0.15 | 0.20 | 0.10 | SSL/TLS, DMARC, SPF, DKIM, HSTS, DNSSEC, CSP, CAA, WAF, security.txt (15 signals) |
| 3 | Governance | 0.20 | 0.23 | 0.10 | Privacy policy, GDPR/CCPA, terms, refund/return, shipping, cookie consent (10 signals) |
| 4 | Transparency | 0.10 | 0.15 | 0.05 | robots.txt, sitemap, Schema.org, hreflang, AI crawler policy, llms.txt, about page |
| 5 | Data Quality | 0.15 | 0.05 | 0.25 | E-commerce: 22 product data signals. SaaS: 12 platform signals (API docs, SLA, pricing, security certs) |
| 6 | Fulfillment | -- | -- | 0.40 | Delivery speed, return window, tracking, shipping policy (COLD mode: not scored) |
What Each Dimension Measures
| Dimension | Evaluates |
|---|
| Verification (V) | Is this a real, registered business? SSL certificate type, GLEIF LEI, Wikidata entity,
Only the beginning is shown; read the rest in the repo