# FRED Economic Data

> Use this tool when you need to access and analyze economic data from the Federal Reserve Bank of St. Louis, solving problems such as retrieving time series data and searching for economic indicators. It provides an interface for querying economic datasets and returns relevant data and metadata, making it ideal for trend analysis, economic research, and data-driven policy recommendations. This tool is particularly useful for economists, financial analysts, and AI developers working on economic modeling or forecasting applications.

Canonical page: https://skillsregistry.net/skills/kablewy-fred-economic-data  
JSON: https://api.skillsregistry.net/v1/skills/kablewy-fred-economic-data

## Description

This FRED (Federal Reserve Economic Data) MCP server provides AI assistants with access to economic data from the Federal Reserve Bank of St. Louis. It integrates with the FRED API to offer tools for retrieving time series data, searching for economic indicators, and obtaining metadata about data series. Built with TypeScript and the @modelcontextprotocol/sdk, it implements automatic rate limiting to comply with FRED's usage guidelines. The server abstracts the complexities of working with economic datasets, allowing AI systems to easily incorporate up-to-date economic indicators into their analyses. It is particularly useful for economists, financial analysts, and AI developers working on economic modeling or forecasting applications, enabling use cases like trend analysis, economic research, and data-driven policy recommendations.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kablewy-fred-economic-data)
- **Repository:** <https://github.com/kablewy/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": "kablewy-fred-economic-data"
    }
  }
}
```

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