Brazil Retail & Fuel Price Intelligence MCP Server
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| 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
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
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.
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.
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.
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.