genpark-agentic-commerce-ucp-catalog-resolver-skill
Provides catalog resolution and agentic checkout capabilities through the Universal Commerce Protocol (UCP), enabling AI agents to query merchant availability and complete machine-to-machine purchases.
Implements AP2 delegated payment tokens with spend limits and zero PAN exposure, and routes settlement through Mastercard Agent Pay.
Participates in Universal Commerce Protocol (UCP) catalog resolution, allowing agents to search merchant catalogs, check multi-merchant availability, and optimize fulfillment SLAs.
Supports AP2-based agentic payment flows, issuing scoped ephemeral payment credentials and handling tokenized settlement for agent-initiated purchases.
Enables UCP catalog resolution and agent-gateway purchasing so autonomous agents can query Target inventory and complete delegated orders.
Provides Agentic Payment Protocol (AP2) integration for cryptographic financial delegation, using ephemeral tokenized credentials with strict spend bounds and no PAN exposure, plus Visa Agent Pay settlement.
Supports UCP-based agentic commerce, exposing product availability and enabling delegated machine-to-machine checkout for Walmart inventory.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@genpark-agentic-commerce-ucp-catalog-resolver-skillfind the best price on a PS5 with 2-day delivery from any merchant"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
genpark-agentic-commerce-ucp-catalog-resolver-skill
Executive Overview & Architectural Motivation
In 2025–2026, Agentic Commerce evolved from experimental in-chat discovery to standardized, machine-to-machine financial execution rails. Spearheaded by the Universal Commerce Protocol (UCP) (Google, Shopify, Walmart, Target), Agentic Payment Protocols (AP2) (Visa, Mastercard, Stripe), and retail Agent Gateways, autonomous AI agents now act as legally delegated consumer proxies.
This skill library distills the core mathematical logic and agent orchestration models powering the GenPark Agentic Commerce Operating System:
Machine-to-Machine Catalog Resolution: Instantaneous multi-merchant availability and Pareto SLA optimization.
Cryptographic Financial Delegation: Ephemeral tokenization with strict spend bounds and zero PAN exposure.
Game-Theoretic Bargaining: Rubinstein alternating-offers automated negotiation with dynamic surplus splitting.
Zero-Dependency Protocol Parity: Full native Model Context Protocol (MCP) compliance for agentic runtime integration.
Related MCP server: merx
Architecture Diagram
flowchart TD
subgraph ConsumerAgent["Consumer AI Agent Layer"]
UserIntent[User Shopping Mandate] --> DelegationVault["AP2 Delegation Vault"]
DelegationVault --> AgentCore["GenParkAgenticCommerceUCPCatalogResolver"]
end
subgraph CommerceProtocols["Agentic Commerce Protocols"]
AgentCore --> UCP["Universal Commerce Protocol (UCP)"]
AgentCore --> A2M["A2M Bargaining Engine"]
AgentCore --> Gateway["Retailer Agent Gateway"]
end
subgraph FulfillmentRails["Execution & Settlement"]
Gateway --> MerchantInventory[Live Merchant Inventory]
Gateway --> TokenizedPayment[Mastercard / Visa Agent Pay]
endTechnical Specifications & Features
Capability | Specification |
Runtime Environment | Python 3.9+ (Standard Library Only) |
External Dependencies | None (0 packages) |
Protocol Compatibility | Anthropic Model Context Protocol (MCP) STDIO JSON-RPC 2.0 |
Architecture Paradigm | Pure Functional & Mathematical Modeling |
Deployment Mode | Headless Agent Skill, CLI Client, or MCP Server |
Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Standalone MCP Server Launch
Run the native STDIO MCP server for Claude Desktop, Cursor, or Antigravity integration:
python mcp_server.py3. Model Context Protocol (MCP) Config
Add to your claude_desktop_config.json or agent runner config:
{
"mcpServers": {
"genpark-agentic-commerce-ucp-catalog-resolver-skill": {
"command": "python",
"args": ["path/to/genpark-agentic-commerce-ucp-catalog-resolver-skill/mcp_server.py"]
}
}
}Frequently Asked Questions (FAQ)
Q1: What makes GenPark Agentic Commerce Skills unique?
Engineered with zero external dependencies using pure Python standard library code. This ensures instantaneous cold starts, sub-millisecond execution overhead, and zero package version conflicts across diverse agent runtime environments.
Q2: How do I test this MCP server locally?
Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.
License
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be deployed
Maintenance
Related MCP Connectors
AI-agent product catalog: search, lookup & purchase routing over verified merchant data.
The independent agent-commerce protocol for AI-agent checkout on any online store.
Agentic commerce gateway: discovery, search, checkout across Shopify/Woo/Odoo/PrestaShop with UCP, ACP, AP2, X402. Checkout rules for agents, and trust receipts.
Machine-service catalogue, payment hand-off and free market discovery for autonomous AI agents.
Related MCP Servers
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to autonomously discover services, negotiate binding quotes, make idempotent purchases, and receive cryptographically verifiable deliverables.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to discover products, verify signed catalog feeds, negotiate within published policies, and place mandate-bound orders with signed receipts via MCP, A2A, or REST.1MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to resolve multi-merchant Universal Commerce Protocol catalogs with Pareto-optimal pricing and SLA routing, while supporting tokenized payment delegation and automated bargaining through MCP tools.7MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to manage ephemeral payment tokens with cryptographic spend mandates, risk scoring, catalog resolution, and automated bargaining through native MCP tools.7MIT