Brazil Retail & Fuel Price Intelligence MCP Server
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- AlicenseNot gradedqualityBmaintenanceEnables agents to query 153 live Brazilian government data tools across federal and state sources, including economy, legislature, judiciary, elections, health, education, and more, reading directly from original APIs.MIT
- AlicenseNot gradedqualityCmaintenanceProvides point-in-time Brazilian market data and official statistics, enabling accurate backtesting and AI agent access to vintage, unrevised data, as well as Brazilian financial primitives like PIX code generation and business day calculations.MIT
- FlicenseNot gradedqualityCmaintenanceProvides business intelligence, compliance tools, and economic data for Latin America, including Brazilian company lookups, tax ID validation for multiple countries, and economic indicators from official government sources.-
- AlicenseNot gradedqualityNot gradedmaintenanceConnects AI agents to 28 Brazilian public APIs, providing over 200 tools to access data on economy, legislation, transparency, and the judiciary. It enables complex queries and cross-referencing of government datasets like IBGE, the Central Bank, and the National Congress through natural language.MIT
- FlicenseBqualityDmaintenanceQuery a variety of data from Brasil resources seamlessly. Access information on postal codes, area codes, banks, holidays, taxes, and more through a unified interface. Enhance your AI agents and applications with rich and updated data from BrasilAPI effortlessly.67-
- AlicenseAqualityAmaintenanceEnables AI assistants to query Brazilian public data from IBGE, Banco Central, INMET, and Câmara dos Deputados, including population, economic indicators, weather observations, and legislative information, without requiring API keys for most tools.1455 PyPI2MIT
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.