venue-ops-mcp
Related Servers
Alternatives to venue-ops-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables read-only investigation of unusual crypto market activity by combining price, volume, volatility, order-book, and correlation signals into explainable anomaly reports and evidence timelines.-
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to query live Toast POS data and generate sales, labor, and cash reports while answering restaurant operations questions, all in a read-only manner.14 npmMIT
- FlicenseBqualityCmaintenanceA secure, read-only MCP server that enables AI assistants to inspect transactions, vendor performance, wallet balances, and analytics through validated REST API calls.19-
- AlicenseNot gradedqualityDmaintenanceA read-only MCP server that enables restaurant staff to query Veloce POS data using natural language, supporting sales summaries, payment breakdowns, and weekly reports.MIT
- AlicenseNot gradedqualityFmaintenanceRead-only Stripe finance, ops, and risk reporting exposed via MCP, HTTP API, and CLI. Enables querying balances, payments, customers, payouts, reconciliation, and risk alerts without mutating Stripe state.MIT
- FlicenseNot gradedqualityCmaintenanceEnables read-only access to Addepar portfolio and ownership data for financial reporting, with transparent provenance caveats and compliance-oriented audit logging.-
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: listing venues, retrieving a single day, comparing to same weekday averages, aggregating a range, and detecting anomalies. There is no overlap or ambiguity between them, and cross-references in examples reinforce which tool to use for which question.
All five tools follow the exact same verb_noun pattern with the venue_ops_ prefix, using snake_case (find_anomalies, list_venues, get_day, compare_weekday, period_summary). The naming is perfectly predictable and consistent.
With 5 tools, the server is well-scoped for a venue operations analytics domain. Each tool earns its place and covers a distinct query pattern without being too thin or unnecessarily heavy.
The tool surface covers the core analytics needs: discovery (list), point-in-time snapshot (get day), fair comparison (compare weekday), aggregation (period summary), and proactive insight (find anomalies). No obvious gaps within the stated purpose of venue analytics.