.stats { display: grid; grid-template-columns: repeat(auto-fit, minmax(160px, 1fr)); gap: 14px; margin-bottom: 40px; } .stat { background: var(--card); border: 1px solid var(--border); border-radius: 8px; padding: 16px 18px; } .stat-n { font-size: 26px; font-weight: 700; color: var(--gold-dim); line-height: 1; } .stat-l { font-size: 10px; color: var(--muted); margin-top: 6px; font-family: ui-monospace, 'SF Mono', Menlo, Consolas, monospace; letter-spacing: 0.9px; text-transform: uppercase; }
h2 { font-size: 11px; text-transform: uppercase; letter-spacing: 1.5px; color: var(--gold-dim); font-family: ui-monospace, 'SF Mono', Menlo, Consolas, monospace; margin: 36px 0 14px; font-weight: 700; } .card { background: var(--card); border: 1px solid var(--border); border-radius: 8px; padding: 18px 22px; margin-bottom: 14px; } .card ul { padding-left: 20px; } .card li { margin: 4px 0; } .card li code { background: var(--gold-bg); color: var(--gold-dim); padding: 1px 6px; border-radius: 4px; font: 13px ui-monospace, 'SF Mono', Menlo, Consolas, monospace; }
.questions { display: grid; gap: 8px; } .q { background: var(--card); border: 1px solid var(--border); border-left: 3px solid var(--gold); border-radius: 4px; padding: 12px 16px; font-size: 15px; color: var(--text); font-style: italic; } .q::before { content: '"'; color: var(--gold); font-weight: 700; } .q::after { content: '"'; color: var(--gold); font-weight: 700; }
pre { background: var(--black); color: var(--gold); border-radius: 6px; padding: 12px 16px; overflow-x: auto; font: 13px ui-monospace, 'SF Mono', Menlo, Consolas, monospace; margin: 8px 0; } .connect-row { display: flex; gap: 24px; flex-wrap: wrap; } .connect-col { flex: 1 1 320px; } .connect-col h3 { font-size: 13px; font-weight: 700; color: var(--text); margin-bottom: 8px; } .connect-col p { font-size: 14px; color: var(--muted); margin-bottom: 8px; }
footer { max-width: 880px; margin: 32px auto 0; padding: 24px 32px; border-top: 1px solid var(--border); color: var(--muted); font-size: 13px; } footer a { color: var(--gold-dim); text-decoration: none; font-weight: 600; } footer a:hover { text-decoration: underline; }
@media (max-width: 600px) { .brand-block { flex-direction: column; align-items: flex-start; gap: 10px; } .header-cta { width: 100%; } main { padding: 24px 20px 48px; } }
NPS Intelligence — MCP
Public Net Promoter Score (NPS) disclosures · Live, citable, in Claude
A remote MCP server that lets Claude (and any other MCP-aware client) query a curated database of publicly disclosed Net Promoter Score (NPS) values from named companies — with source URLs, news snippets, and pre-computed sector benchmarks across 1,000+ industries.
Try asking Claude
Tools exposed
lookup_company— every disclosed NPS for a named company, with citationssearch_disclosures— filter by sector, year range, and qualityget_sector_benchmark— pre-computed mean / median / p75 / min / max per sectorlist_coverage— what the database actually contains
Connect
Claude.ai (browser)
Settings → Connectors → Add custom connector.
https://cg-nps-mcp.adam-dorrell.workers.dev/mcp
Claude Desktop (Mac/Win)
Uses mcp-remote proxy with the /sse endpoint.
https://cg-nps-mcp.adam-dorrell.workers.dev/sse
Power users — install the skill
The MCP server ships its own instructions automatically — every client that connects gets the citation rules, tool guidance, and disclosure-bias framing without any extra install. But if you want the same rules applied locally (e.g. when working with an exported CSV), grab the skill as a markdown file:
curl -o ~/.claude/skills/cg-nps/SKILL.md https://cg-nps-mcp.adam-dorrell.workers.dev/skill
Why this is interesting
Claude doesn't know what specific companies have published about their NPS. This MCP gives it 15 years of curated public disclosures with a source URL on every row — so any answer Claude gives can be verified, and any company named is grounded in a real news article or investor document. It's the evidence layer that turns "what's a typical NPS?" from a guess into a citation.