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MCP-FREDAPI

by Jaldekoa

Data/Analytics & ProcessingFREDAPIEconomic DataClaudeCursor

MCP-FREDAPI provides access to economic data from the Federal Reserve Bank of St. Louis (FRED) through the Model Context Protocol. This integration allows AI assistants like Claude to retrieve economic time series data directly when used with Cursor or other MCP-compatible environments.

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What is MCP-FREDAPI?

MCP-FREDAPI is an integration that allows AI assistants to access economic data from the Federal Reserve Bank of St. Louis (FRED) through the Model Context Protocol (MCP). It focuses on the series_observations endpoint of the FRED API, providing time series data for economic indicators.

How to use MCP-FREDAPI?

  1. Install the package using pip or uv. 2. Obtain a FRED API key and store it in a .env file. 3. Configure Cursor (or another MCP-compatible environment) to use the MCP server by adding the server configuration to your ~/.cursor/mcp.json file. 4. Use the @mcp-fredapi:get_fred_series_observations tool in Claude/Cursor with appropriate parameters to retrieve data.

Key features of MCP-FREDAPI

  • Access to FRED economic data

  • Integration with Model Context Protocol

  • Time series data retrieval

  • Compatibility with Claude and Cursor

  • Configurable data transformations (units)

  • Frequency control for data aggregation

Use cases of MCP-FREDAPI

  • Retrieving GDP data

  • Analyzing inflation rates

  • Accessing consumer price index data

  • Obtaining economic indicators for AI models

  • Comparing economic trends over time

FAQ from MCP-FREDAPI

What is FRED?

FRED (Federal Reserve Economic Data) is a database maintained by the Federal Reserve Bank of St. Louis containing economic time series data.

How do I get a FRED API key?

You can obtain a FRED API key from the FRED API website (https://fred.stlouisfed.org/docs/api/api_key.html).

Which parameters are currently working?

The working parameters are: series_id, sort_order, units, frequency, aggregation_method, and output_type.

Which parameters are not working?

The non-working parameters are: realtime_start, realtime_end, limit, offset, observation_start, observation_end, and vintage_dates.

How do I contribute to this project?

Fork the repository, create a feature branch, make your changes, commit them, push to your branch, and open a pull request.