# FRED (Federal Reserve Economic Data)

> Use this tool when you need to retrieve authoritative U.S. economic indicators, such as Overnight Reverse Repurchase Agreements and Consumer Price Index data, for financial analysis, economic research, or data-driven decision making. It provides customizable parameters for date ranges, observation limits, and sorting options, and handles API authentication for easy consumption. The FRED tool outputs formatted economic time series data, making it a valuable resource for accessing reliable economic information.

Canonical page: https://skillsregistry.net/skills/stefanoamorelli-fred  
JSON: https://api.skillsregistry.net/v1/skills/stefanoamorelli-fred

## Description

FRED MCP Server provides a bridge to the Federal Reserve Economic Data API, enabling AI assistants to retrieve economic time series data. Developed by Stefano Amorelli, it currently supports tools for accessing Overnight Reverse Repurchase Agreements (RRPONTSYD) and Consumer Price Index (CPIAUCSL) datasets with customizable parameters for date ranges, observation limits, and sorting options. The server is built with TypeScript using the Model Context Protocol SDK, handles API authentication, and formats responses for easy consumption. This implementation is particularly valuable for financial analysis, economic research, and data-driven decision making where access to authoritative U.S. economic indicators is needed.

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** security
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/stefanoamorelli-fred)
- **Repository:** <https://github.com/stefanoamorelli/fred-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "stefanoamorelli-fred"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/stefanoamorelli-fred` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/stefanoamorelli-fred/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt