Agenticfeed

Name: Agenticfeed
Author: bluestratus

by bluestratusversion 0.2.0i★ –iRuns in the cloud

Registry nameio.github.bluestratus/agenticfeed

Install

Overview

Description from the maker (original English)

Match shopper intent to a merchant's products and fetch live price, stock and product Q&A.

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 in the cloud
Transport: Streamable HTTP
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 the maker’s server: what you ask it goes through their server.
The registry lists no key to fill in.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

Open Settings → Connectors
Press Add custom connector
Paste the address below and press Add
If it asks you to sign in, sign in with the maker

https://agenticfeed.ai/mcp

Run this in your terminal

claude mcp add --transport http agenticfeed https://agenticfeed.ai/mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "agenticfeed": {
      "url": "https://agenticfeed.ai/mcp"
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "agenticfeed": {
      "type": "http",
      "url": "https://agenticfeed.ai/mcp"
    }
  }
}

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.

ChatGPT connects only to servers on the internet:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://agenticfeed.ai/mcp

Menu names can differ slightly by plan and over time.

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

We have not read this server’s tool list yet; we check endpoints in rotation.

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 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account bluestratus, 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 checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Online shops & paymentsi

More stars than 0% of the other 1751 servers in this category
Published to the registry more recently than 21% of the other 1751 servers in this category
Basic checks equal to or better than 100% of the other 1751 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 Agenticfeed 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 in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.0) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

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

Spree Commerce: open-source B2B and marketplace ecommerce

by spree

Open-source B2B and marketplace ecommerce; new stores include an MCP server for AI agents.

Runs in the cloud★ 15,812BSD-3-ClauseUpdated 7 days ago

Install

Stripe MCP

by stripe

Stripe’s official server lets AI view and manage customers, products, payments and invoices. Connect to Stripe’s cloud and sign in with OAuth.

Runs in the cloud★ 2,043MITUpdated 12 months ago

Install

MCP Cn Commerce

by TonyWang-hub

8 read-only MCP platform entries; support is operation-specific; merchant live acceptance pending

Runs on your computer★ 96MITUpdated 28 days ago

Install

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.

Agenticfeed Standard

An open specification for making ecommerce product catalogues readable by AI shopping agents.

AI assistants like ChatGPT, Claude, Perplexity, and Gemini are already recommending products to millions of shoppers. They do not browse category pages or read banner ads. They consume structured data and reason about which products best match the buyer's intent. Most merchant websites are invisible to them.

This standard defines a lightweight, discoverable format that gives AI agents exactly what they need.

Quick start

Add one line to the of every page on your website:

<link rel="agenticfeed" type="application/json" href="https://yourdomain.com/feed.json">

That tag tells any AI agent or crawler where your structured product feed lives. The rest of this document describes what that feed should contain.

What is an agentic feed?
Why does this standard exist?
How is it different from a Google Merchant Center feed?
How do AI agents discover it?
How do I add it to my website?
Specification
1. Discovery tag
2. Feed index
3. Intent endpoints
4. Product detail
5. UTM attribution
6. Link validation
Agent Query API
Authentication
Request
Response
Agent Card
Examples
Reference implementation
Contributing
Licence

What is an agentic feed?

An agentic feed is a structured product data feed built for AI agents rather than search engine crawlers or human browsers.

A traditional product page is designed to be rendered and read by a person. A Google Merchant Center feed is designed to be parsed by a price comparison engine. An agentic feed is designed to be reasoned about by an AI.

The key difference is intent data. Where a merchant feed tells an agent "here is a cordless drill, it costs £29.99 and it is in stock," an agentic feed tells it "here is a cordless drill that answers the question *what drill do I need for assembling flat-pack furniture*, solves the problem *I keep stripping screws with my old drill*, and fits the use case *home DIY for a first-time homeowner*."

That is the layer of context an AI agent needs to make a confident recommendation to a specific buyer.

Why does this standard exist?

AI shopping is already happening. The tooling to serve it well does not yet exist as an open, portable standard.

Search engines standardised web content discovery through sitemaps, robots.txt, and canonical tags. RSS standardised content syndication through a single autodiscovery tag. Neither was designed for the kind of structured reasoning that AI agents perform when they decide what to recommend.

This specification fills that gap. It defines:

How a website signals to AI agents that a structured product feed exists
What format that feed takes
How intent data (questions, problems, use cases) is structured alongside standard product data
How AI agents navigate from a buyer's query to a specific product recommendation

The format is intentionally minimal. It builds on schema.org types that crawlers already understand. It adds the intent layer that makes AI recommendation possible.

How is it different from a Google Merchant Center feed?

	Google Merchant Center feed	Agenticfeed
Format	XML (RSS-like)	JSON-LD
Schema	Google's proprietary spec	schema.org + agenticfeed namespace
Primary consumer	Price comparison, Shopping ads	AI agents, LLMs, shopping assistants
Discovery	Manual URL submission	Autodiscovery via
Intent data	None	Questions, problems, use cases per product
Product context	Price, title, image, availability	Price, title, image + buyer intent layer
Attribution	None built in	UTM parameters on every product URL

A Google Merchant Center feed tells a machine *what* a product is. An agentic feed tells it *why a specific buyer should choose it*.

The two are complementary. Many merchants use a GMC feed as the data source for generating an agentic feed.

How do AI agents discover it?

The discovery mechanism follows the same autodiscovery pattern the web has used for decades:

rel="stylesheet"   tells browsers where to find CSS

rel="icon" tells browsers where to find the favicon rel="alternate" tells crawlers where to find RSS feeds rel="agenticfeed" tells AI agents where to find structured product data

When an AI agent or crawler visits a merchant's website, it reads the page . If it finds a rel="agenticfeed" tag, it knows exactly where to fetch structured product data without being told the URL in advance.

This means:

No manual registration with each AI platform
No API keys or access agreements required
Any AI agent that implements this standard can discover your feed automatically
The merchant controls the data at their own URL

How do I add it to my website?

Step 1. Add the discovery tag to every page :

<link rel="agenticfeed" type="application/json" href="https://yourdomain.com/feed.json">

Step 2. Serve a JSON-LD feed index at that URL (see examples/feed.json):

"@context": "https://schema.org", "@type": "DataFeed", "name": "Your Store Name", "url": "https://yourdomain.com/feed.json", "provider": { "@type": "Organization", "name": "Agenticfeed", "url": "https://agenticfeed.ai" }, "dataFeedElement": [ { "@type": "DataFeedItem", "name": "Questions", "url": "https://yourdomain.com/questions.json" }, { "@type": "DataFeedItem", "name": "Problems", "url": "https://yourdomain.com/problems.json" }, { "@type": "DataFeedItem", "name": "Use Cases", "url": "https://yourdomain.com/use-cases.json" } ] }

Step 3. Serve intent endpoints for each category (see examples/questions.json).

Step 4. Serve product detail documents for each product (see examples/product.json).

For Shopify merchants, agenticfeed.ai handles all of this automatically including injecting the discovery tag into your theme.

Specification

1. Discovery tag

<link rel="agenticfeed" type="application/json" href="{absolute-url-to-feed-index}">

Attribute	Value
`rel`	`agenticfeed`
`type`	`application/json`
`href`	Absolute URL to the feed index document

Place this tag in the of every page. It must appear in the server-rendered HTML, not injected by JavaScript, so crawlers can find it without executing scripts.

2. Feed index

Content-Type: application/ld+json Schema.org type: DataFeed

The feed index is the entry point for any agent reading your feed. It identifies the merchant, lists intent endpoints, and provides the URL template for resolving individual products.

See examples/feed.json for a complete example.

Agent workflow:

Find the discovery tag in the page
Fetch the feed index
Read dataFeedElement to find intent endpoints
Fetch the relevant endpoint based on the buyer's query type
Match intent entries to the buyer's need and extract product IDs
Resolve each product ID using the agenticfeed.resolution.product.url template
Fetch the product detail document

3. Intent endpoints

Intent endpoints are JSON-LD ItemList documents grouped by product category. There are three intent types:

Questions — natural language questions a buyer asks before purchasing. Schema.org type: Question with suggestedAnswer pointing to the product URL. See examples/questions.json

Problems — pain points or needs the product addresses. Schema.org type: ListItem with name (the problem) and url (the product). See examples/problems.json

Use cases — specific scenarios or goals the product fits. Schema.org type: ListItem with name (the use case) and url (the product). See examples/use-cases.json

4. Product detail

Content-Type: application/ld+json Schema.org type: Product

Each product has its own document at a stable URL. It combines standard schema.org Product data with the intent content under an agenticfeed namespace.

See examples/product.json for a complete example.

Field	Type	Description
`@context`	string	`https://schema.org`
`@type`	string	`Product`
`name`	string	Product title
`url`	string	Merchant product page URL (UTM-tagged)
`image`	string	Primary product image URL
`category`	string	Product category
`offers`	Object	schema.org `Offer` — price, currency, availability
`agenticfeed.questions`	Array	Questions this product answers
`agenticfeed.problems`	Array	Problems this product solves
`agenticfeed.use_cases`	Array	Use cases this product fits

5. UTM attribution

All product URLs in an agentic feed should carry UTM parameters so merchants can measure AI agent traffic in their analytics:

utm_source=agenticfeed&utm_medium=ai-agent

This lets merchants filter and report on sessions and orders that originated from an AI agent recommendation in Google Analytics, Shopify Analytics, or any platform that reads UTM parameters.

6. Link validation

The discovery tag in the merchant's serves as proof of domain ownership before a feed goes live. A validator fetches the merchant's homepage, parses the , and confirms:

A rel="agenticfeed" tag is present
Its href matches the expected feed URL for that merchant

This prevents one merchant from claiming another merchant's domain in a feed.

Agent Query API

The passive feed endpoints let AI agents crawl product data at their own pace. The Agent Query API is the active layer — an AI agent or application can send a natural language buyer intent and receive back a ranked list of matched products with reasons.

This is agent-to-agent communication. Instead of a human typing into a search box, one AI asks another AI to find the best matching products.

Endpoint

POST https://agenticfeed.ai/agent/query

Content-Type: application/json Authorization: Bearer af_your_api_key

Authentication

One API key is required:

Agenticfeed API key — passed as a Bearer token in the Authorization header. This identifies who is making the request and controls access to the feed data. Generate one in Dashboard › API Keys for any paid plan (Growth and above). No approval needed — keys are available instantly.

Request

"query": "ergonomic chair for someone with lower back pain, works from home 10 hours a day, small home office, budget under £300", "customer_guid": "a9a8378c94", "limit": 5 }

Field	Type	Required	Description

| query | string | Yes | Natural language description of what the bu

Only the beginning is shown; read the rest in the repo

Agenticfeed

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Online shops & paymentsi

Common questions

Alternatives

Spree Commerce: open-source B2B and marketplace ecommerce

Stripe MCP

MCP Cn Commerce

README from the maker

Agenticfeed Standard

Quick start

Contents

What is an agentic feed?

Why does this standard exist?

How is it different from a Google Merchant Center feed?

How do AI agents discover it?

How do I add it to my website?

Specification

1. Discovery tag

2. Feed index

3. Intent endpoints

4. Product detail

5. UTM attribution

6. Link validation

Agent Query API

Authentication

Request