Integrations
Used for configuration to securely store and access the FRED API key through environment variables
MCP-FREDAPI
FRED (Federal Reserve Economic Data) API integration with Model Context Protocol (MCP)
Table of Contents
Introduction
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.
This package integrates with the official FRED API, focusing specifically on the series_observations endpoint which provides time series data for economic indicators.
Installation
There are two installation methods:
Method 1: Using pip
Install the required dependencies:
Clone this repository:
Method 2: Using uv (Recommended)
This method is recommended as it matches the configuration shown in mcp.json.
- First, install uv if you don't have it yet:
- Clone this repository:
- Use uv to run the server (no need to install dependencies separately):
Configuration
FRED API Key
You'll need a FRED API key, which you can obtain from FRED API.
Create a .env
file in the project root:
Claude/Cursor Configuration
To configure Cursor to use this MCP server, add the following to your ~/.cursor/mcp.json
file:
Replace /path/to/mcp-fredapi
with the actual path to the repository on your system. For example:
Note: On Windows, you can use either forward slashes /
or double backslashes \\
in the path.
Available Tools
get_fred_series_observations
Retrieves economic time series observations from FRED.
When using Claude in Cursor, you can access this tool directly with:
Parameters
The get_fred_series_observations
tool accepts the following parameters. For complete technical details about each parameter, please refer to the official FRED API documentation.
Parameter | Type | Description | Allowed Values | Default Value | Status |
---|---|---|---|---|---|
series_id | str | The ID of the economic series | - | (Required) | ✅ Works |
sort_order | str | Sort order of observations | 'asc', 'desc' | 'asc' | ✅ Works |
units | str | Data value transformation | 'lin', 'chg', 'ch1', 'pch', 'pc1', 'pca', 'cch', 'cca', 'log' | 'lin' | ✅ Works |
frequency | str | Frequency of observations | 'd', 'w', 'bw', 'm', 'q', 'sa', 'a', 'wef', 'weth', 'wew', 'wetu', 'wem', 'wesu', 'wesa', 'bwew', 'bwem' | None | ✅ Works |
aggregation_method | str | Aggregation method for frequency | 'avg', 'sum', 'eop' | 'avg' | ✅ Works |
output_type | int | Output type of observations | 1, 2, 3, 4 | 1 | ✅ Works |
realtime_start | str | Start of real-time period (YYYY-MM-DD) | - | None | ❌ Not working |
realtime_end | str | End of real-time period (YYYY-MM-DD) | - | None | ❌ Not working |
limit | int/str | Maximum number of observations to return | Between 1 and 100000 | 10 | ❌ Not working |
offset | int/str | Number of observations to skip from the beginning | - | 0 | ❌ Not working |
observation_start | str | Start date of observations (YYYY-MM-DD) | - | None | ❌ Not working |
observation_end | str | End date of observations (YYYY-MM-DD) | - | None | ❌ Not working |
vintage_dates | str | Comma-separated list of vintage dates | - | None | ❌ Not working |
Warning
Note on Parameter Compatibility
Due to current limitations with the MCP implementation, only certain parameters are working properly:
- ✅ Working parameters:
series_id
,sort_order
,units
,frequency
, aggregation_method, and
output_type`. - ❌ Non-working parameters:
realtime_start
,realtime_end
,limit
,offset
,observation_start
,observation_end
, andvintage_dates
.
For best results, stick with the working parameters in your queries. Future updates may resolve these limitations.
Examples
Getting US GDP Data
When using Claude in Cursor, you can ask for GDP data like this:
Getting GDP Data in Descending Order
Getting Annual GDP Data
Getting Inflation Rate
To get consumer price index data with percent change:
Different Output Format
Contributing
Contributions are welcome. Please follow these steps:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature
) - Make your changes
- Commit your changes (
git commit -m 'Add an amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
License
This project is licensed under the MIT License - see the LICENSE file for details.
References
- FRED API Documentation - Series Observations - Official documentation for the FRED API endpoint used in this project.
- FRED API - Information on obtaining an API key and general API documentation.
- Model Context Protocol - Documentation for the Model Context Protocol.
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Provides access to economic data from the Federal Reserve Bank of St. Louis (FRED) through the Model Context Protocol, allowing AI assistants to retrieve economic time series data directly.
- Table of Contents
- Introduction
- Installation
- Configuration
- Available Tools
- Parameters
- Examples
- Contributing
- License
- References