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Federal Reserve MCP Server logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 7:18:27 PM

Federal Reserve MCP Server

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website

Search and fetch ~800K Federal Reserve economic time-series from the FRED API via MCP.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "federal-reserve-mcp-server": {
      "command": "bunx",
      "args": [
        "@cyanheads/federal-reserve-mcp-server@latest"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

@cyanheads/federal-reserve-mcp-server

Search and fetch ~800K Federal Reserve economic time-series from the FRED API via MCP. STDIO or Streamable HTTP.

8 Tools

Version License Docker MCP SDK npm TypeScript Bun

Install in Claude Desktop Install in Cursor Install in VS Code

Framework


Tools

Five FRED tools plus three DataCanvas tools for querying spilled observation results via SQL:

ToolDescription
fedreserve_search_seriesFull-text search across FRED series titles, units, frequency, and tags β€” returns matching series IDs with metadata
fedreserve_get_seriesFetch metadata for one or more series (title, units, frequency, seasonal adjustment, observation range)
fedreserve_get_observationsFetch date+value observation data for one or more series with date-range filtering and unit transformations
fedreserve_browse_categoriesNavigate the FRED category tree; drill into a category to see child categories and a series sample
fedreserve_get_releaseLook up a FRED release by ID or name search β€” returns release metadata and its associated series list
fedreserve_dataframe_describeList active DataCanvas dataframes registered by this server (canvas IDs, row counts, schemas)
fedreserve_dataframe_queryRun a SELECT query against a registered DataCanvas dataframe
fedreserve_dataframe_dropDrop a DataCanvas dataframe by name (opt-in via FRED_DATAFRAME_DROP_ENABLED=true)

fedreserve_search_series

Search for FRED series by free-text query across titles, tags, and notes.

  • Full-text and series-ID search modes
  • Post-search filtering by frequency, units, or seasonal adjustment status
  • Tag-name filtering (semicolon-delimited list)
  • Pagination via limit and offset
  • To find series for a specific release, use fedreserve_get_release instead

fedreserve_get_series

Fetch metadata for one or more FRED series.

  • Accepts up to 50 series IDs in a single call
  • Returns title, units, frequency, seasonal adjustment, observation range, popularity, and notes
  • Fires parallel upstream requests (no FRED batch endpoint exists); partial success reported per ID

fedreserve_get_observations

Fetch observation data (date + value pairs) for one or more series.

  • Accepts up to 10 series IDs; fires one upstream request per series in parallel
  • Date-range filtering with ISO 8601 dates (observation_start, observation_end)
  • FRED's native unit transformations: lin, chg, ch1, pch, pc1, pca, cch, cca, log
  • Frequency downsampling with configurable aggregation method (avg, sum, eop)
  • Multi-series or >500-row results spill to a DataCanvas table; response includes a dataset.name handle for SQL querying via fedreserve_dataframe_query
  • Degrades gracefully when DataCanvas is unavailable β€” returns inline preview with row count

fedreserve_browse_categories

Navigate the FRED category hierarchy.

  • Omit category_id to start at the root (ID 0)
  • Provide a category_id to see child categories and a series sample for leaf categories
  • Covers all FRED domains: Money & Banking, National Accounts, Employment, Prices, Housing, Trade, and more

fedreserve_get_release

Inspect a FRED data release and its associated series.

  • Look up by release_id (integer) or release_search (case-insensitive substring match)
  • Name search fetches all releases and filters client-side (FRED has no server-side release search)
  • Returns release name, link, scheduled dates, and a paginated series list
  • Use series_limit and series_offset to page through large releases

Features

Built on @cyanheads/mcp-ts-core:

  • Declarative tool definitions β€” single file per tool, framework handles registration and validation
  • Unified error handling across all tools
  • Pluggable auth (none, jwt, oauth)
  • Swappable storage backends: in-memory, filesystem, Supabase, Cloudflare KV/R2/D1
  • Structured logging with optional OpenTelemetry tracing
  • STDIO and Streamable HTTP transports

FRED-specific:

  • Read-only access to the St. Louis Fed's FRED API (api.stlouisfed.org/fred)
  • Parallel multi-series fetching via Promise.allSettled with partial success reporting
  • DataCanvas spillover for multi-series or large observation results β€” spilled tables queryable via fedreserve_dataframe_query
  • Retry with backoff and 429 rate-limit detection against FRED's 120 req/min limit
  • FRED's native unit transformations delegated server-side for precision against the full series history

Getting started

Add the following to your MCP client configuration file. Obtain a free FRED API key at research.stlouisfed.org/docs/api/api_key.html.

config.json
{
  "mcpServers": {
    "federal-reserve-mcp-server": {
      "type": "stdio",
      "command": "bunx",
      "args": ["@cyanheads/federal-reserve-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info",
        "FRED_API_KEY": "your-api-key"
      }
    }
  }
}

Or with npx (no Bun required):

config.json
{
  "mcpServers": {
    "federal-reserve-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cyanheads/federal-reserve-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info",
        "FRED_API_KEY": "your-api-key"
      }
    }
  }
}

Or with Docker:

config.json
{
  "mcpServers": {
    "federal-reserve-mcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "MCP_TRANSPORT_TYPE=stdio",
        "-e", "FRED_API_KEY=your-api-key",
        "ghcr.io/cyanheads/federal-reserve-mcp-server:latest"
      ]
    }
  }
}

For Streamable HTTP, set the transport and start the server:

sh
MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 FRED_API_KEY=... bun run start:http
# Server listens at http://localhost:3010/mcp

Prerequisites

  • Bun v1.3.2 or higher.
  • A free FRED API key from stlouisfed.org. The key grants 120 requests/minute.

Installation

  1. Clone the repository:
sh
git clone https://github.com/cyanheads/federal-reserve-mcp-server.git
  1. Navigate into the directory:
sh
cd federal-reserve-mcp-server
  1. Install dependencies:
sh
bun install
  1. Configure environment:
sh
cp .env.example .env
# edit .env and set FRED_API_KEY

Configuration

All configuration is validated at startup via Zod schemas in src/config/server-config.ts.

VariableDescriptionDefault
FRED_API_KEYRequired. API key from stlouisfed.org.β€”
FRED_BASE_URLOverride the FRED API base URL.https://api.stlouisfed.org/fred
FRED_DATASET_TTL_SECONDSSliding TTL for DataCanvas-registered observation tables (seconds).86400
FRED_DATAFRAME_DROP_ENABLEDSet true to expose the fedreserve_dataframe_drop tool.false
CANVAS_PROVIDER_TYPESet to duckdb to enable DataCanvas SQL querying for observation results.β€”
MCP_TRANSPORT_TYPETransport: stdio or http.stdio
MCP_HTTP_PORTPort for HTTP server.3010
MCP_AUTH_MODEAuth mode: none, jwt, or oauth.none
MCP_LOG_LEVELLog level (RFC 5424).info
LOGS_DIRDirectory for log files (Node.js only).<project-root>/logs
STORAGE_PROVIDER_TYPEStorage backend.in-memory
OTEL_ENABLEDEnable OpenTelemetry instrumentation.false

See .env.example for the full list of optional overrides.

Running the server

Local development

  • Build and run:

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Federal Reserve MCP Server

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "federal-reserve-mcp-server": { "command": "npx", "args": ["-y", "federal-reserve-mcp-server"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
36Quality signal: Fair Β· 36/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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