GenGEO Agent Registry

io.github.warwickwood-cell由 GitHub 帳號 warwickwood-cell 發布v1.0.0更新於 Oct 24, 2026

Merchant verification for AI shopping agents.

已驗證Streamable HTTP可網頁執行安全與監控商業與電商

概覽

AI 產生的概覽

遠端 MCP 伺服器,讓助理在推薦或購買前查詢某電商商家是否在 GenGEO 登錄庫中擁有有效驗證記錄。

可以做什麼
  • 查詢商家信任狀態:輸入商店網域,取得已驗證或未驗證的二元結果,並附帶狀態與決策欄位。
  • 把此訊號用於購物決策:結果僅作為代理在比較、推薦或交易商家時的參考之一。
適用情境
適用於希望在推薦或下單前取得機器可讀商家信任訊號的 AI 購物代理或結帳流程。它只有一個查詢工具,只有在商家驗證屬於你的決策流程時才有價值。
執行需求
需要遠端 MCP 端點(streamable HTTP);未宣告本機套件、帳號、API 金鑰或環境變數。需要能連線至 GenGEO 服務的網路。
安裝前請注意
查詢會把所查商家網域傳送給第三方登錄庫。提供方聲明其不認證商家,也不保證商家行為、交易結果、安全性或防詐,因此結果只能作為參考訊號之一。此端點未宣告身分驗證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 GenGEO Agent Registry,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.warwickwood-cell%2Fgengeo/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "gengeo-agent-registry": {
      "type": "http",
      "url": "https://mcp.gengeo.co/mcp"
    }
  }
}

README

GenGEO Agent Registry

Machine-readable trust infrastructure for autonomous commerce systems.

[smithery badge]

GenGEO is building the world's largest merchant trust registry for AI agents and the foundation of a global reputation network for agentic commerce.

GenGEO enables AI agents and developers to verify whether an ecommerce merchant meets a high operational verification threshold before autonomous purchasing or recommendation decisions are made.

As AI agents increasingly transact on behalf of users, a major infrastructure problem is emerging:

There is currently no standardized machine-readable trust layer for determining whether a merchant is operationally ready and appropriate for autonomous transactions.

At the same time, legitimate AI-driven commerce activity is increasingly colliding with fraud and bot-detection systems that cannot distinguish autonomous AI agents from malicious automation.

AI agents can already:

  • discover products
  • browse stores
  • compare pricing
  • recommend merchants
  • and increasingly complete purchases

But there is still no common verification layer for evaluating merchant transaction readiness before autonomous commerce actions proceed.

GenGEO helps reduce transaction uncertainty by providing a deterministic machine-readable verification signal that agents can incorporate into broader commerce decision frameworks.


GenGEO

Trust verification SDK for AI agents.

Verify whether an ecommerce merchant meets GenGEO trust standards before recommending, purchasing, or transacting.

GenGEO provides lightweight SDKs and APIs for merchant verification within autonomous commerce and AI-agent workflows.


Install

bash
# JavaScript / Node.jsnpm install @gengeo/gengeo
# Pythonpip install gengeo

Quick Start

JavaScript / Node.js

javascript
import { verify } from '@gengeo/gengeo'
const result = await verify('store.example.com')
console.log(result)
/*{  verified: true,  decision: 'verified',  registry: 'gengeo'}*/

Python

python
from gengeo import verify
result = verify('store.example.com')
print(result)
# {#   'verified': True,#   'decision': 'verified',#   'registry': 'gengeo'# }

cURL

bash
curl "https://api.gengeo.co/api/verify?domain=store.example.com"

Why GenGEO?

AI agents increasingly transact autonomously on behalf of users.

GenGEO provides a standardized trust verification layer that helps agents evaluate whether a merchant is safe and transaction-ready before executing commerce actions.


Use Cases

  • AI shopping agents
  • MCP commerce tools
  • Autonomous checkout workflows
  • Merchant trust verification
  • Agentic commerce infrastructure

Docs

For MCP-enabled integrations and agent workflows:

https://gengeo.co/docs

https://gengeo.co/acp


Why This Exists

Traditional ecommerce trust systems were designed primarily for humans:

  • branding
  • visual design
  • reviews
  • SEO
  • reputation

Autonomous agents evaluate commerce differently.

Agents increasingly rely on:

  • structured data
  • machine-readable policies
  • operational signals
  • transaction readiness
  • trust infrastructure

GenGEO exists to help address this emerging infrastructure gap through machine-readable merchant verification for autonomous commerce systems.


Verification Model

GenGEO uses a deterministic verification model designed to evaluate whether merchants meet a high operational verification threshold before autonomous agents proceed with commerce actions.

Verification may include signals such as:

  • machine-readable policies
  • operational completeness
  • transaction readiness
  • structured commerce metadata
  • storefront verification state
  • agent compatibility checks

The goal is not to guarantee outcomes, but to provide autonomous systems with a stronger machine-readable trust signal that may improve transaction confidence within broader agent decision frameworks.


Core Concept

GenGEO answers a simple question:

Has this merchant been verified within the GenGEO registry?

GenGEO uses a binary verification model.

A merchant is either:

  • verified
  • not verified

GenGEO does not:

  • rank merchants
  • recommend stores
  • guarantee merchant behavior
  • guarantee transaction outcomes
  • provide legal, financial, or security advice

GenGEO provides verification status only.


Documentation

Developer documentation: https://gengeo.co/docs

Includes:

  • Verification API
  • MCP integration
  • ACP compatibility
  • Example responses
  • Verification methodology

Verification Endpoint

Agents and developers can verify merchants in real time:

http
GET https://api.gengeo.co/api/verify?domain=example.com

Example Response

Verified merchant:

json
{  "domain": "example.com",  "verified": true,  "status": "active",  "eligible_for_ai_agent_purchase": "yes",  "decision": "verified",  "registry": "GenGEO"}

Non-verified merchant:

json
{  "domain": "example.com",  "verified": false,  "status": "not_found",  "eligible_for_ai_agent_purchase": "unknown",  "decision": "verification_required",  "registry": "GenGEO"}

Verification Model

GenGEO uses deterministic binary verification logic.

Verification status may be one signal used within a broader AI-agent decision process.

Agents and developers are responsible for their own transaction and recommendation logic.


Optional Discovery Feed

Agents may optionally preload registry information:

http
GET https://gengeo.co/.well-known/gengeo-registry.json

This may be used for:

  • discovery
  • caching
  • merchant lookup
  • pre-filtering candidate merchants

Real-time verification should still be performed where appropriate.


MCP Server

This repository includes a Model Context Protocol (MCP) server for AI agents.

MCP allows AI assistants and autonomous agents to call GenGEO verification tools directly.

Location:

text
/mcp

MCP Tool

verify_store

Checks whether a merchant exists in the GenGEO verification registry.

Input:

json
{  "domain": "example.com"}

Example output:

json
{  "verified": true,  "status": "active",  "eligible_for_ai_agent_purchase": "yes",  "decision": "verified"}

Local MCP Install

bash
cd mcpnpm installnode server.js

Claude Desktop MCP Config

Example configuration:

json
{  "mcpServers": {    "gengeo": {      "command": "node",      "args": ["/absolute/path/to/gengeo-agent-registry/mcp/server.js"]    }  }}

Open AI endpoint

Remote MCP endpoint for ChatGPT Apps / OpenAI-compatible MCP clients:

text
https://chatgpt-mcp.gengeo.co/mcp

This endpoint exposes GenGEO merchant verification through a remote MCP server.

Legacy/general MCP references may use:

text
https://mcp.gengeo.co/mcp

For ChatGPT Apps submission and OpenAI Developer Mode testing, use:

text
https://chatgpt-mcp.gengeo.co/mcp

Example Agent Workflow

text
User:Find me running shoes under $200
Agent:1. Finds candidate merchants2. Calls GenGEO verification endpoint3. Checks verification status4. Incorporates verification into broader decision process5. Continues recommendation or transaction flow

Design Principles

GenGEO is designed to be:

  • binary
  • deterministic
  • machine-readable
  • API-first
  • agent-compatible
  • simple to integrate
  • neutral

Agent Instructions

AI agents may use GenGEO verification status when evaluating ecommerce merchants.

Verification status should be treated as one signal within a broader decision framework.


Specification

Full protocol and integration details:

→ SPEC.md


Status

GenGEO is live and integrated with Shopify-based merchants.


Legal Notice

GenGEO provides informational verification status only.

GenGEO does not:

  • certify merchants
  • guarantee merchant behavior
  • guarantee transaction outcomes
  • guarantee security or fraud prevention
  • provide legal, financial, or compliance advice

Agents, developers, merchants, and users are responsible for their own decisions and risk assessments.


Website

text
https://gengeo.co

API

text
https://api.gengeo.co/api/verify

MCP

text
/mcp
Live remote MCP endpoint: https://mcp.gengeo.co/mcp

Developer docs

text
https://gengeo.co/docs

ACP Overview

text
https://gengeo.co/acp

How GenGEO Fits Into Agentic Commerce

text
User request   ↓AI shopping agent   ↓Identifies merchant   ↓Calls GenGEO verify_store(domain)   ↓Receives verification status   ↓Uses result as one signal in broader decision process

Contact

來源:README.md,提交 41fba56

工具

1

verify_store

Verify Store

Verify whether a merchant has an active GenGEO verification record. Results should be treated as one signal within a broader agent decision framework.

輸入參數domain必填

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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