MCP-FREDAPI

FRED (Federal Reserve Economic Data) API integration with Model Context Protocol (MCP)

Table of Contents

• Introduction
• Installation
• Configuration
  • FRED API Key
  • Claude/Cursor Configuration
• Available Tools
• Parameters
• Examples
  • Common Economic Series IDs
• Contributing
• License
• References

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:

pip install "mcp[cli]" httpx python-dotenv

Clone this repository:

git clone https://github.com/Jaldekoa/mcp-fredapi.git
cd mcp-fredapi

Method 2: Using uv (Recommended)

This method is recommended as it matches the configuration shown in mcp.json.

1. First, install uv if you don't have it yet:

pip install uv

2. Clone this repository:

git clone https://github.com/Jaldekoa/mcp-fredapi.git
cd mcp-fredapi

3. Use uv to run the server (no need to install dependencies separately):

uv run --with mcp --with httpx mcp run server.py

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:

FRED_API_KEY=your_api_key_here

Claude/Cursor Configuration

To configure Cursor to use this MCP server, add the following to your ~/.cursor/mcp.json file:

{
  "mcpServers": {
    "mcp-fredapi": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-fredapi", "run", "--with", "mcp", "--with", "httpx", "mcp", "run", "server.py"]
    }
  }
}

Replace /path/to/mcp-fredapi with the actual path to the repository on your system. For example:

{
  "mcpServers": {
    "mcp-fredapi": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-fredapi", "run", "--with", "mcp", "--with", "httpx", "mcp", "run", "server.py"]
    }
  }
}

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:

@mcp-fredapi:get_fred_series_observations

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.

[!WARNING]

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, and vintage_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:

Can you get the latest GDP data from FRED?

@mcp-fredapi:get_fred_series_observations
{
  "series_id": "GDP"
}

Getting GDP Data in Descending Order

Can you get the GDP data in descending order (newest first)?

@mcp-fredapi:get_fred_series_observations
{
  "series_id": "GDP",
  "sort_order": "desc"
}

Getting Annual GDP Data

Can you get annual GDP data?

@mcp-fredapi:get_fred_series_observations
{
  "series_id": "GDP",
  "frequency": "a"
}

Getting Inflation Rate

To get consumer price index data with percent change:

What's the recent inflation rate in the US?

@mcp-fredapi:get_fred_series_observations
{
  "series_id": "CPIAUCSL",
  "units": "pch",
  "frequency": "m"
}

Different Output Format

Show me GDP data in a different format.

@mcp-fredapi:get_fred_series_observations
{
  "series_id": "GDP",
  "output_type": 2
}

Contributing

Contributions are welcome. Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Commit your changes (git commit -m 'Add an amazing feature')
5. Push to the branch (git push origin feature/amazing-feature)
6. 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.