Bar Assistant MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| BAR_ASSISTANT_URL | Yes | Base URL of your Bar Assistant instance | |
| BAR_ASSISTANT_TOKEN | Yes | API authentication token for Bar Assistant | |
| BAR_ASSISTANT_BAR_ID | No | Bar ID to use in Bar Assistant (optional, defaults to 1) | 1 |
| BAR_ASSISTANT_API_KEY | No | API authentication key for Bar Assistant (alternative to token) |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| smart_search_cocktailsA | 🚀 PREFERRED TOOL: Advanced cocktail search with intelligent batch processing and complete recipes. 🎯 BATCH PROCESSING SYSTEM:
📋 Use Cases:
🔄 Batch Processing Examples:
📊 Response Format: Returns structured data with complete recipes including:
⚡ Performance Features:
|
| get_recipeA | 🍸 Advanced recipe retrieval with powerful batch processing for multiple cocktails. 🚀 BATCH PROCESSING SYSTEM:
📋 LLM Usage Patterns:
🎯 Input Methods (Choose Based on Use Case):
📊 Response Format: Structured output with complete recipe data:
⚡ Performance Examples:
🎛️ Batch Control Parameters:
|
| get_ingredient_infoA | Get comprehensive information about cocktail ingredients and their usage. Use Cases:
Response Format: Returns detailed ingredient information including:
Examples:
|
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 3 tools
The three tools have distinct primary purposes: get_ingredient_info focuses on ingredient details and substitutions, get_recipe retrieves specific cocktail recipes, and smart_search_cocktails searches for cocktails based on various criteria. However, there is some functional overlap between get_recipe and smart_search_cocktails, as both can return complete recipes, which could cause minor confusion for an agent deciding which to use for recipe retrieval.
The tool names follow a consistent verb_noun pattern (get_ingredient_info, get_recipe, smart_search_cocktails), which is clear and predictable. The only minor deviation is that smart_search_cocktails uses an adjective (smart) before the verb_noun structure, but this is still readable and maintains overall consistency.
With three tools, this server is well-scoped for a bar assistant domain, covering key areas like ingredient information, recipe retrieval, and cocktail search. Each tool serves a distinct and valuable function, and the count is neither too sparse nor overwhelming, making it easy for an agent to navigate and use effectively.
The toolset covers core functionalities for a bar assistant, such as ingredient lookup, recipe fetching, and cocktail search. However, there are notable gaps in the lifecycle coverage; for example, there are no tools for creating, updating, or managing cocktails or ingredients (e.g., add_recipe, update_ingredient), which limits the server's utility for more interactive or creative tasks beyond retrieval and search.