// may the 4th be with you⚔️
financeanalytics-data

FRED (Federal Reserve Economic Data)

by stefanoamorelli

Access FRED to retrieve economic time series data, including the consumer confidence index and composite leading indicat

Provides a bridge to the Federal Reserve Economic Data API for retrieving economic time series data like Overnight Reverse Repurchase Agreements and Consumer Price Index with customizable parameters for date ranges and sorting options.

github stars

65

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

800,000+ official Fed datasetsComprehensive economic indicators coverage

best for

  • / Economic research and analysis
  • / Financial modeling and forecasting
  • / Academic research on monetary policy
  • / Investment analysis and market research

capabilities

  • / Query economic time series data from FRED
  • / Retrieve inflation and unemployment statistics
  • / Access interest rates and monetary policy data
  • / Filter data by custom date ranges
  • / Sort economic indicators by various parameters
  • / Search across 800,000+ economic datasets

what it does

Connects to the Federal Reserve Economic Data API to retrieve and analyze economic time series data like inflation rates, unemployment figures, and other financial indicators. Provides access to 800,000+ official economic datasets from the Fed.

about

FRED (Federal Reserve Economic Data) is a community-built MCP server published by stefanoamorelli that provides AI assistants with tools and capabilities via the Model Context Protocol. Access FRED to retrieve economic time series data, including the consumer confidence index and composite leading indicat It is categorized under finance, analytics data.

how to install

You can install FRED (Federal Reserve Economic Data) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

AGPL-3.0

FRED (Federal Reserve Economic Data) is released under the AGPL-3.0 license.

readme

Federal Reserve Economic Data MCP Server

smithery badge npm version DOI License: AGPL v3 Tests

[!IMPORTANT] Disclaimer: This open-source project is not affiliated with, sponsored by, or endorsed by the Federal Reserve or the Federal Reserve Bank of St. Louis. "FRED" is a registered trademark of the Federal Reserve Bank of St. Louis, used here for descriptive purposes only.

A Model Context Protocol (MCP) server providing universal access to all 800,000+ Federal Reserve Economic Data (FRED®) time series through three powerful tools.

https://github.com/user-attachments/assets/66c7f3ad-7b0e-4930-b1c5-a675a7eb1e09

[!TIP] If you use this project in your research or work, please cite it using the CITATION.cff file, or use the following citation:

APA Format:

Amorelli, S. (2025). Federal Reserve Economic Data MCP (Model Context Protocol) Server (Version 1.0.2) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.14536707

BibTeX:

@software{amorelli_2025_14536707,
  author       = {Amorelli, Stefano},
  title        = {{Federal Reserve Economic Data MCP (Model Context
                   Protocol) Server}},
  month        = jan,
  year         = 2025,
  publisher    = {Zenodo},
  version      = {1.0.2},
  doi          = {10.5281/zenodo.14536707},
  url          = {https://doi.org/10.5281/zenodo.14536707}
}

Installation

Installing via Smithery

To install Federal Reserve Economic Data Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @stefanoamorelli/fred-mcp-server --client claude

Manual Installation

  1. Clone the repository:
    git clone https://github.com/stefanoamorelli/fred-mcp-server.git
    cd fred-mcp-server
    
  2. Install dependencies:
    pnpm install
    
  3. Build the project:
    pnpm build
    

Configuration

This server requires a FRED® API key. You can obtain one from the FRED® website.

Install the server, for example, on Claude Desktop, modify the claude_desktop_config.json file and add the following configuration:

{
  "mcpServers": {
    "FRED MCP Server": {
      "command": "/usr/bin/node",
      "args": [
        "<PATH_TO_YOUR_CLONED_REPO>/fred-mcp-server/build/index.js"
      ],
      "env": {
        "FRED_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

Using Docker

You can also run the FRED MCP Server using Docker. Add this configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "fred-mcp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "FRED_API_KEY=<your-key-here>",
        "stefanoamorelli/fred-mcp-server:latest"
      ],
      "env": {}
    }
  }
}

Replace <your-key-here> with your actual FRED API key.

Using Streamable HTTP Transport

For network deployments, you can run the server with Streamable HTTP transport instead of stdio:

# Using CLI flag
node build/index.js --http

# Or using environment variable
TRANSPORT=http node build/index.js

# Custom port (default is 3000)
PORT=8080 node build/index.js --http

The server will be available at http://localhost:3000/mcp (or your custom port).

Example client request:

# Initialize session
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"my-client","version":"1.0.0"}}}'

# Use the mcp-session-id from the response header for subsequent requests
curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: <session-id-from-init>" \
  -d '{"jsonrpc":"2.0","id":2,"method":"tools/list"}'

Available Tools

This MCP server provides three comprehensive tools to access all 800,000+ FRED® economic data series:

fred_browse

Description: Browse FRED's complete catalog through categories, releases, or sources.

Parameters:

  • browse_type (required): Type of browsing - "categories", "releases", "sources", "category_series", "release_series"
  • category_id (optional): Category ID for browsing subcategories or series within a category
  • release_id (optional): Release ID for browsing series within a release
  • limit (optional): Maximum number of results (default: 50)
  • offset (optional): Number of results to skip for pagination
  • order_by (optional): Field to order results by
  • sort_order (optional): "asc" or "desc"

fred_search

Description: Search for FRED economic data series by keywords, tags, or filters.

Parameters:

  • search_text (optional): Text to search for in series titles and descriptions
  • search_type (optional): "full_text" or "series_id"
  • tag_names (optional): Comma-separated list of tag names to filter by
  • exclude_tag_names (optional): Comma-separated list of tag names to exclude
  • limit (optional): Maximum number of results (default: 25)
  • offset (optional): Number of results to skip for pagination
  • order_by (optional): Field to order by (e.g., "popularity", "last_updated")
  • sort_order (optional): "asc" or "desc"
  • filter_variable (optional): Filter by "frequency", "units", or "seasonal_adjustment"
  • filter_value (optional): Value to filter the variable by

fred_get_series

Description: Retrieve data for any FRED series by its ID with support for transformations and date ranges.

Parameters:

  • series_id (required): The FRED series ID (e.g., "GDP", "UNRATE", "CPIAUCSL")
  • observation_start (optional): Start date in YYYY-MM-DD format
  • observation_end (optional): End date in YYYY-MM-DD format
  • limit (optional): Maximum number of observations
  • offset (optional): Number of observations to skip
  • sort_order (optional): "asc" or "desc"
  • units (optional): Data transformation:
    • "lin" (levels/no transformation)
    • "chg" (change from previous period)
    • "ch1" (change from year ago)
    • "pch" (percent change)
    • "pc1" (percent change from year ago)
    • "pca" (compounded annual rate of change)
    • "cch" (continuously compounded rate of change)
    • "log" (natural log)
  • frequency (optional): Frequency aggregation ("d", "w", "m", "q", "a")
  • aggregation_method (optional): "avg" (average), "sum", or "eop" (end of period)

Example Usage

With these three tools, you can:

  • Browse all economic categories and discover available data
  • Search for specific indicators by keywords or tags
  • Retrieve any of the 800,000+ series with custom transformations
  • Access real-time economic data including GDP, unemployment, inflation, interest rates, and more

Social Media Shoutouts 📣

[!NOTE] Want to be featured? Tag Stefano Amorelli on LinkedIn or @stefanoamorelli on X in your post about using FRED MCP Server, or submit a PR to add your shoutout!

We're grateful for the community support! Here are some mentions from amazing people:

<details open> <summary><b>Scott G</b> - "One of my breakthrough moments for 'getting' what is possible with Claude was this fred-mcp-server project..."</summary> <br> <a href="https://www.linkedin.com/posts/sgoley_as-many-of-us-continue-to-use-llms-more-and-activity-7372401049669885952-ha6M"> <img src="assets/social/linkedin-sgoley.jpg" alt="LinkedIn post by Scott G - Fintech & Data Analytics Professional" width="600"> </a> <br> <i>Scott G - Fintech & Data Analytics Professional</i> | <a href="https://www.linkedin.com/in/sgoley/">LinkedIn Profile</a> </details> <details open> <summary><b>John Shelburne</b> - "The FRED MCP Server is a game-changer for financial analysis..."</summary> <br> <a href="https://www.linkedin.com/posts/shelburne_ai-finance-innovation-activity-7341141860880478210-JQe4"> <img src="assets/social/linkedin-john-shelburne.jpg" alt="LinkedIn post by John Shelburne" width="600"> </a> <br> <i>John Shelburne - Fixed Income Fintech Leader with 20+ Years of Experience | Machine Learning & Cloud Computing Specialist</i> | <a href="https://www.linkedin.com/in/shelburne/">LinkedIn Profile</a> </details> <!-- Add more social media posts here using the format above -->

Testing

See TESTING.md for more details.

# Run all tests
pnpm test

# Run specific tests
pnpm test:registry

License ⚖️

This open-source project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). This means:

  • You can use, modify, and distribute this software
  • If you modify and distribute it, you must release your changes under AGPL-3.0
  • If you run a modified version on a server, you must provide the source code to users
  • See the LICENSE file for full details

For commercial licensing options or other licensing inquiries, please contact stefano@amorelli.tech.

© 2025 [Stefano Amorelli](https://


FAQ

What is the FRED (Federal Reserve Economic Data) MCP server?
FRED (Federal Reserve Economic Data) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for FRED (Federal Reserve Economic Data)?
This profile displays 30 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Discussion

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MCP server reviews

Ratings

4.830 reviews
  • Omar Rahman· Dec 20, 2024

    FRED (Federal Reserve Economic Data) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Hiroshi Ramirez· Dec 12, 2024

    FRED (Federal Reserve Economic Data) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Shikha Mishra· Dec 8, 2024

    FRED (Federal Reserve Economic Data) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Rahul Santra· Nov 27, 2024

    Useful MCP listing: FRED (Federal Reserve Economic Data) is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Lucas Bhatia· Nov 15, 2024

    Strong directory entry: FRED (Federal Reserve Economic Data) surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Yash Thakker· Nov 11, 2024

    I recommend FRED (Federal Reserve Economic Data) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Michael Sanchez· Nov 11, 2024

    According to our notes, FRED (Federal Reserve Economic Data) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Neel Rahman· Nov 3, 2024

    Useful MCP listing: FRED (Federal Reserve Economic Data) is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Hiroshi Martin· Oct 22, 2024

    FRED (Federal Reserve Economic Data) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Hiroshi Yang· Oct 6, 2024

    I recommend FRED (Federal Reserve Economic Data) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

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