Restaurant Ops MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| calculate_menu_item_metricsB | Calculate food cost and contribution margin for one menu item. Args: selling_price: Realized selling price per unit, excluding tax and tips. ingredient_cost: Direct ingredient cost for one unit. units_sold: Number of units sold in the period being analyzed. |
| analyze_menu_csvA | Analyze menu economics from CSV text. The CSV must include these columns: item,selling_price,ingredient_cost,units_sold Returns menu-level totals and items ranked by total contribution margin. Costs are theoretical recipe costs, not measured purchases or inventory usage. Contribution excludes labor, rent, fees, waste, and other operating costs. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools operate at different granularities: one calculates metrics for a single item, while the other parses and analyzes a full menu CSV. There is minor conceptual overlap because both compute contribution margin, but the input format and output scope are sufficiently distinct.
Both names use snake_case and follow a verb_noun pattern (calculate_menu_item_metrics, analyze_menu_csv). The convention is consistent and readable throughout.
The server name implies broader restaurant operations, but only two narrow menu-economics tools are provided. While the pair covers single-item and batch analysis, the surface feels thin for the stated scope.
For menu economics, item-level and menu-level contribution analysis covers the core workflow. Minor gaps exist around period comparisons, pricing scenarios, or export/reporting, but agents can work around them.