
Fred Mcp Server
io.github.stefanoamorelli由 GitHub 帳號 stefanoamorelli 發布v1.0.1更新於 Oct 24, 2026
Federal Reserve Economic Data (FRED) MCP Server - Access all 800,000+ economic time series
概覽
讓助理瀏覽、搜尋並取得美國聯準會經濟資料(FRED)時間序列,包括 GDP、失業率與通膨等指標。
- 可以做什麼
- 透過三個工具存取 FRED 超過 80 萬筆經濟時間序列。fred_browse 可瀏覽分類、發布與來源,或列出某分類或發布下的序列。fred_search 可依關鍵字、序列 ID 或標籤尋找序列,並依頻率、單位與季節調整篩選。fred_get_series 依序列 ID 取得觀測值,支援日期範圍、頻率聚合以及百分比變化、自然對數等轉換。
- 適用情境
- 適合助理需要美國官方總體經濟資料進行研究、報告或分析的場合,例如取得 GDP 或 CPI 歷史資料、比較指標,或查找某個主題下有哪些序列。
- 執行需求
- 以本機 Node.js 程序執行(npm 套件 fred-mcp-server),也可用 Docker 執行;需要 FRED API 金鑰,透過環境變數 FRED_API_KEY 提供。需要連線至 FRED API 的網路存取。可透過 TRANSPORT、HOST 與 PORT 啟用選用的 HTTP 傳輸模式。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Fred Mcp Server,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Federal Reserve Economic Data MCP Server
[npm version] [DOI] [License: AGPL v3] [Tests] [Documentation]
[!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:
BibTeX:
Installation
Manual Installation
- Clone the repository:
- Install dependencies:
- Build the project:
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:
Using Docker
You can also run the FRED MCP Server using Docker. Add this configuration to your claude_desktop_config.json:
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:
The server will be available at http://localhost:3000/mcp (or your custom port).
Example client request:
A GET /healthz endpoint reports active sessions, cache statistics, and uptime for load balancers and orchestrators.
Configuration
All settings are environment variables with sensible defaults:
Identical concurrent requests are coalesced into a single upstream call, and successful responses are cached, so multiple sessions share one rate-limit budget efficiently.
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 categoryrelease_id(optional): Release ID for browsing series within a releaselimit(optional): Maximum number of results (default: 50)offset(optional): Number of results to skip for paginationorder_by(optional): Field to order results bysort_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 descriptionssearch_type(optional): "full_text" or "series_id"tag_names(optional): Comma-separated list of tag names to filter byexclude_tag_names(optional): Comma-separated list of tag names to excludelimit(optional): Maximum number of results (default: 25)offset(optional): Number of results to skip for paginationorder_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 formatobservation_end(optional): End date in YYYY-MM-DD formatlimit(optional): Maximum number of observationsoffset(optional): Number of observations to skipsort_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:
Scott G - "One of my breakthrough moments for 'getting' what is possible with Claude was this fred-mcp-server project..."
[LinkedIn post by Scott G - Fintech & Data Analytics Professional]
Scott G - Fintech & Data Analytics Professional | LinkedIn Profile
John Shelburne - "The FRED MCP Server is a game-changer for financial analysis..."
[LinkedIn post by John Shelburne]
John Shelburne - Fixed Income Fintech Leader with 20+ Years of Experience | Machine Learning & Cloud Computing Specialist | LinkedIn Profile
Testing
See TESTING.md for more details.
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 [email protected].
© 2025 Stefano Amorelli
來源:README.md,提交 cb1db30
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1- v1.0.1最新Sep 16, 2026
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