MCP CPG Knowledge Graph
io.github.greencore-solutions/cpg-knowledge-graphCPG Knowledge Graph: product, brand, manufacturer, retail, market and procurement intelligence
Tools · 14
Resolve a GTIN to its procurement readiness signal. Zero-pads input to 14 digits.
Check whether a GTIN can ship to a specific retailer banner in a country.
Return the full ACM-68000 signal chain for a GTIN (zero-pads to 14).
Global coverage statistics: GTINs, nodes, makers (supply), retailers (demand).
GSC Scoped Agents Registry — Era 1 founding registry (1,000,000 standing) plus Era 2 station-keyed registry (1,000,000 capacity, mint-on-activation) under SM-ECO-10060.
The 49 sovereign nodes (the spine) — each with its GS1 GTIN and CLEAN per-node maker (supply) and retailer (demand) counts (separate subqueries, never summed).
Resolve one node: its GS1 license + its makers (supply) + its retailers (demand).
Global cross-node maker (supply) search. Filter by segment / region / node / has_website.
Global cross-node retailer (demand) search. Filter by region / node / parent_banner.
Supply↔demand bridge for ONE jurisdiction: makers (supply) and retailers (demand) as two separate counts (never summed), plus the same-node potential bridge pairs.
SPARKS taxonomy: the 84 standing BPC product-type codes the graph is structured on. Validate a type against this before a typed query. (BRAND is a tier, not a type.)
SPARKS depth surface: the distinct brands SPARKS covers in a sovereign market. Answers 'what brands do you know in [node]'. Coverage only — no pack/size values.
SPARKS completeness tier for a brand in a market: 100 = resolvable (a real pack/size record is held) . 8 = registered (brand known, pack/size pending) . 'floor' = STANDARD default (no brand-specif…
Two-branch SPARKS resolver (zero-pads GTIN to 14). Branch A GSC Territory/License GTIN (990832300xxx) -> FULL license record (public). Branch B any third-party BPC GTIN -> GATED proof {recognize…
Similar MCP servers embedding-nearest
How to use
Add to your Claude Desktop / Cursor / Cline MCP config:
{
"mcpServers": {
"mcp_cpg_knowledge_graph": {
"url": "https://mcp.cpgknowledgegraph.ai/mcp",
"transport": "streamable-http"
}
}
}