Skip to main content

Agentic Product Protocol MCP Server

Klarna-style product discovery for AI shopping agents.

Makes product catalogs machine-readable so AI agents can search, compare, and purchase products programmatically — no screen scraping, no landing pages.

The Problem

Today's e-commerce is built for humans: landing pages, image carousels, "Add to Cart" buttons. AI shopping agents can't efficiently navigate this. They need structured product data — not HTML.

Klarna introduced the Agentic Product Protocol (December 2025) to solve exactly this: a standardized way for merchants to expose their product catalogs to AI agents. Think of it as RSS feeds, but for shopping.

What This Server Does

This MCP server implements the core ideas of agentic product discovery:

  • Structured search results — not web pages, but clean JSON with name, price, nutrition, ratings
  • Product comparison — side-by-side structured comparison across multiple dimensions
  • Feed conversion — take any product feed (JSON, CSV, Open Food Facts) and normalize it into an agent-friendly schema
  • Schema generation — convert raw product data into the Agentic Product Protocol format
  • Availability checking — real-time product status in a machine-readable format

Uses Open Food Facts as a demo data source — works with any product feed.

Installation

pip install agentic-product-protocol-mcp

Or with uvx (no install needed):

uvx agentic-product-protocol-mcp

Configuration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "product-protocol": {
      "command": "uvx",
      "args": ["agentic-product-protocol-mcp"]
    }
  }
}

Claude Code (CLI)

claude mcp add product-protocol -- uvx agentic-product-protocol-mcp

Tools

Tool Description
search_products Search products with structured results (name, nutrition, labels, stores)
get_product_details Get full product data by barcode/ID
compare_products Side-by-side comparison of 2-5 products
convert_feed Convert JSON/CSV/OFF feeds into normalized agent schema
generate_product_schema Generate Agentic Product Protocol schema from raw data
check_availability Check product availability and store information

Example Usage

Search for products:

"Search for organic chocolate bars"

Compare products:

"Compare these three chocolate bars: 3017620422003, 7622210449283, 7613034626844"

Convert a feed:

"Convert this Open Food Facts search into agent-friendly format: https://world.openfoodfacts.org/cgi/search.pl?search_terms=protein+bar&page_size=10"

Generate schema:

"Generate an agentic product schema for this product data: {name: 'Widget Pro', price: 29.99, category: 'Electronics'}"

Why Structured Feeds > Landing Pages

Landing Pages Structured Feeds
Parsing Screen scraping, fragile Clean JSON, reliable
Speed Load page → parse DOM → extract Single API call
Accuracy Layout changes break everything Schema-validated
Comparison Manual extraction per site Normalized across sources
Agent UX Built for human eyes Built for agent consumption

Data Source

This server uses Open Food Facts as its demo data source — a free, open, community-built database of food products from around the world. No API key required.

For production use, connect your own product feeds using the convert_feed tool with JSON or CSV format.

License

MIT

Metadata

Release files for agentic-product-protocol-mcp 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for agentic-product-protocol-mcp 0.1.0
File Size Uploaded
agentic_product_protocol_mcp-0.1.0.tar.gz 10.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for agentic-product-protocol-mcp 0.1.0
File Interpreter ABI Platform
agentic_product_protocol_mcp-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 22.9 kB

Release files / agentic_product_protocol_mcp-0.1.0.tar.gz

Download URL agentic_product_protocol_mcp-0.1.0.tar.gz
Size 10.1 kB
Tags Source
SHA-256 checksum
How to use checksums
a9e623436841a3eb985c925665e2a43f15a0af301095134cfea4379fdbf145fd
BLAKE2b-256 checksum
How to use checksums
2b549ad1002fab30cd58436c228767b6bcc6cfd0a87ae01e0a9239fb340d6dee
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.13.3

Release files / agentic_product_protocol_mcp-0.1.0-py3-none-any.whl

Download URL agentic_product_protocol_mcp-0.1.0-py3-none-any.whl
Size 12.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
e5da8ec39c0c5dad1d8db3f90cf192571608c04be1b31b170c6297aab17979c2
BLAKE2b-256 checksum
How to use checksums
42d2c5b55c2573fb9f4562fe9aa44d7276e2bfdfdc206a8f99e66d0bb44211c3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.13.3

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page