FipeX MCP

What fipeX MCP MCP server does

The fipeX MCP MCP server is intended for working with Brazilian vehicle reference prices based on the FIPE table. The listed capabilities are vehicle search, current-price lookup, historical price access, and comparison. These capabilities fit applications that need to identify a vehicle and inspect how its reference value changes across FIPE reference periods.

The underlying project covers vehicles sold in Brazil, including cars, motorcycles, and trucks. Its records include the FIPE code, make, model, fuel type, model year, zero-kilometre status, price in centavos, a formatted Brazilian-real value, and the reference month and year. This makes the data usable for both direct lookups and analysis based on vehicle attributes or time.

The project is independent and is not affiliated with Fundação Instituto de Pesquisas Econômicas. Its data is derived from publicly available FIPE information and is supplied without an absolute accuracy guarantee, so results should be treated carefully in financially significant decisions.

How it works

The related fipeX project maintains a free public API for accessing automotive data. The API is described as requiring no key and allowing up to 10 requests per IP address per second. The supplied material does not specify endpoint paths, request schemas, response formats, or the MCP protocol transport used by the listing.

Historical data is also distributed as monthly FIPE-period dumps and complete release snapshots. Each monthly dump represents the original names published for that period. Complete snapshots are available in original and merged forms. Original records preserve historical model names, while merged records apply current model naming across historical periods, which is useful when tracking one vehicle through renamings.

The dataset contains 12 shared fields. Prices are stored as integer centavos to avoid floating-point issues, with a separate formatted currency field for readability. Reference month and year fields allow consumers to group or compare values over time.

Setup and configuration

No API key is required for the public fipeX API according to the supplied project information. The material does not provide an MCP installation command, package name, configuration file, command-line entry point, or environment variables for running the server. It also does not document client-specific setup.

For direct data work, the project publishes release assets on GitHub and mirrors the dataset on Hugging Face. Full snapshots are available as CSV and Parquet. The CSV files use tab separators rather than commas. Parquet is described as the preferred format for analytical workflows using tools such as Python, Polars, Pandas, Spark, or DuckDB.

Tools and capabilities

The documented capabilities are:

• Search Brazilian FIPE vehicle records.
• Retrieve a vehicle's current reference price.
• Inspect historical prices by FIPE reference period.
• Compare vehicle prices or price histories.
• Work with vehicle attributes such as make, model, fuel, year, and vehicle category.

The supplied README does not list formal MCP tool names or argument definitions. Treat the capability list above as functional scope rather than an API schema.

Limitations and notes

The repository material describes a dataset and a public API, but it does not explain how the MCP server is packaged or hosted. There is no documented transport, client compatibility list, tool schema, authentication configuration, or error model. The fipeX MCP MCP server should therefore be evaluated against those operational requirements before deployment.

The data is intended for analysis and applications using FIPE reference values, not as a guarantee of a transaction price. Monthly updates are intended as new FIPE tables become available, but the supplied material does not promise a fixed update schedule or real-time values.

Original and merged snapshots answer different historical questions. Use original data when preserving the names published at each period matters. Use merged data when following a model across historical renamings is more important. The project is released under CC0-1.0, and the dataset may be used commercially without required attribution.