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Glama
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Brazil Retail & Fuel Price Intelligence MCP Server

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
brazil_fuel_pricesA

Queries real-time audited fuel prices (Gasoline, Ethanol, Diesel S10, CNG) from Brazil ANP across 4,750+ stations in all 27 states.

brazil_grocery_basketB

Queries and compares audited prices of Brazil's basic food basket sourced from electronic consumer invoices (NFC-e SEFAZ).

cost_of_living_brazilB

Returns consolidated regional cost-of-living index and purchasing power parity (BRL/USD) in Brazil.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.4/5.0

Scored across 3 tools

Disambiguation4/5

Each tool targets a distinct dataset: fuel prices, grocery basket, and cost-of-living index. There is mild conceptual overlap between brazil_grocery_basket and cost_of_living_brazil (both touch on consumer costs), but the descriptions make the boundary reasonably clear.

Naming Consistency3/5

Two tools follow a 'brazil_<noun>' prefix pattern (brazil_fuel_prices, brazil_grocery_basket), but cost_of_living_brazil puts the country at the end instead. Readable overall, but the pattern breaks in a small set where consistency is easy to achieve.

Tool Count3/5

Three tools is thin for a data-intelligence server covering multiple datasets. Each tool earns its place, but the surface feels like a minimal MVP rather than a well-rounded set.

Completeness3/5

All three tools are read-only queries with no apparent supporting operations such as listing covered states, stations, time ranges, or comparing regions across datasets. The core query surface exists, but agents will hit dead ends for discovery and drill-down tasks.

Maintenance

ActivityMaintained
ResponsivenessNo issues