For developers & AI agents
Agentic e-commerce on live shelf data
Digishelf is building MCP connectors and APIs so agents and applications can query retailer shelf data programmatically—price, availability, content, and competitive context without brittle scrapers.
MCP connectors for e-commerce data
Model Context Protocol servers let AI assistants discover and invoke tools safely. Digishelf MCP tools wrap our normalized shelf layer so agents answer questions like “where did MAP break?” or “which competitor dropped price in DE?” with grounded data.
MCP-ready shelf data
Expose normalized digital shelf datasets as tools your agents can call—structured for LLMs, not scraped HTML.
REST & warehouse feeds
Pull the same data into pipelines, notebooks, or BI. One schema for humans, agents, and automation.
Agentic workflows
Wire Digishelf into Cursor, Claude, or custom copilots to monitor, explain, and act on shelf changes.
Example MCP tools (preview)
// digishelf-mcp server
{
"tools": [
{
"name": "search_listings",
"description": "Find SKUs by brand, category, or retailer with live shelf metadata."
},
{
"name": "get_price_history",
"description": "Time-series price and promotion signals for a product across markets."
},
{
"name": "check_availability",
"description": "Stock and fulfillment status by retailer and region."
},
{
"name": "compare_content",
"description": "Title, bullets, images, and ratings vs. your PIM or competitors."
}
]
}Get early access
MCP connectors and developer APIs are rolling out with design partners. If you want programming access to Digishelf shelf data—for agents, apps, or internal tools—leave your contact and tell us what you're building.
- ✓MCP server + REST endpoints
- ✓Typed schemas for price, promo, OOS, and content
- ✓Sandbox keys for pilot retailers