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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
lookup_foodA

Nutrition values for an Indian food (calcium, fibre, iron, protein) per 100 g and per katori, with the source article URL, for 59 foods. Data from ICMR-NIN composition tables.

compare_foodsB

Compare several Indian foods side by side on one nutrient (calcium, fibre, iron, protein; default protein).

protein_targetB

Daily protein target in grams for a given body weight and age, using ICMR-NIN and PROT-AGE guidance, plus the per-meal threshold.

protein_costA

Cost of protein in India ranked cheapest first, in rupees per 10 g of protein, across whole foods and supplements.

search_guidesA

Search 1,152 Indian nutrition guides by topic and return titles with URLs, for citation.

list_productsA

KABO's own nutrition shakes: per-serving protein, calories, fibre and vitamins for each flavour, with ratings and product URLs.

get_productA

One KABO product in full: per-serving nutrition from its own panel, composition quoted from the product page, dietary suitability, live price and stock per pack size, price per serving, and a cart link or UCP checkout profile.

compare_productsA

KABO products side by side with live price per serving. Omit products to compare all.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 8 tools

Disambiguation4/5

The tools split cleanly along resource lines: single food (lookup_food) vs multi-food (compare_foods), product list (list_products) vs single product (get_product) vs side-by-side (compare_products), plus two clearly separate protein calculators (target vs cost). The only mild overlaps are list_products vs compare_products (both surface per-serving macros across products) and lookup_food vs compare_foods when only one food is compared.

Naming Consistency4/5

Most names follow a verb_noun pattern (lookup_food, compare_foods, search_guides, list_products, get_product, compare_products) and are all snake_case. The two protein tools (protein_target, protein_cost) break the verb-first convention by being noun phrases, a minor but noticeable deviation.

Tool Count5/5

Eight tools is well within the sweet spot and each maps to a distinct job: single lookup, comparison, two calculators, guide search, and a three-tool product sub-surface. Nothing feels padded or redundant.

Completeness3/5

Product coverage is a full read lifecycle (list/get/compare with live price), but the 59-food database has no list or search-by-name/criteria tool, so an agent must already know exact food names to use lookup_food or compare_foods. search_guides returns titles and URLs only, with no tool to fetch a guide's content, leaving dead ends for citation depth.

Maintenance

ActivityMaintained
ResponsivenessNo issues