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@Cyanheads/Federal Reserve Server

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

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Описание

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

README

@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


Tools

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

Tool Description
fedreserve_search_series Full-text search across FRED series titles, units, frequency, and tags — returns matching series IDs with metadata
fedreserve_get_series Fetch metadata for one or more series (title, units, frequency, seasonal adjustment, observation range)
fedreserve_get_observations Fetch date+value observation data for one or more series with date-range filtering and unit transformations
fedreserve_browse_categories Navigate the FRED category tree; drill into a category to see child categories and a series sample
fedreserve_get_release Look up a FRED release by ID or name search — returns release metadata and its associated series list
fedreserve_dataframe_describe List active DataCanvas dataframes registered by this server (canvas IDs, row counts, schemas)
fedreserve_dataframe_query Run a SELECT query against a registered DataCanvas dataframe
fedreserve_dataframe_drop Drop 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 — 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 — 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 — 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.

{
  "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):

{
  "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:

{
  "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:

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

Prerequisites

Installation

  1. Clone the repository:
git clone https://github.com/cyanheads/federal-reserve-mcp-server.git
  1. Navigate into the directory:
cd federal-reserve-mcp-server
  1. Install dependencies:
bun install
  1. Configure environment:
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.

Variable Description Default
FRED_API_KEY Required. API key from stlouisfed.org.
FRED_BASE_URL Override the FRED API base URL. https://api.stlouisfed.org/fred
FRED_DATASET_TTL_SECONDS Sliding TTL for DataCanvas-registered observation tables (seconds). 86400
FRED_DATAFRAME_DROP_ENABLED Set true to expose the fedreserve_dataframe_drop tool. false
CANVAS_PROVIDER_TYPE Set to duckdb to enable DataCanvas SQL querying for observation results.
MCP_TRANSPORT_TYPE Transport: stdio or http. stdio
MCP_HTTP_PORT Port for HTTP server. 3010
MCP_AUTH_MODE Auth mode: none, jwt, or oauth. none
MCP_LOG_LEVEL Log level (RFC 5424). info
LOGS_DIR Directory for log files (Node.js only). <project-root>/logs
STORAGE_PROVIDER_TYPE Storage backend. in-memory
OTEL_ENABLED Enable OpenTelemetry instrumentation. false

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

Running the server

Local development

  • Build and run:

    # One-time build
    bun run rebuild
    
    # Run the built server
    bun run start:stdio
    # or
    bun run start:http
    
  • Run checks and tests:

    bun run devcheck   # Lint, format, typecheck, security
    bun run test       # Vitest test suite
    bun run lint:mcp   # Validate MCP definitions against spec
    

Docker

docker build -t federal-reserve-mcp-server .
docker run --rm -e FRED_API_KEY=your-key -e MCP_TRANSPORT_TYPE=http -p 3010:3010 federal-reserve-mcp-server

The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/federal-reserve-mcp-server. OpenTelemetry peer dependencies are installed by default — build with --build-arg OTEL_ENABLED=false to omit them.

Project structure

Directory Purpose
src/index.ts createApp() entry point — registers tools and inits services.
src/config Server-specific environment variable parsing and validation with Zod.
src/mcp-server/tools Tool definitions (*.tool.ts). Eight tools across FRED domain and DataCanvas.
src/services/fred FRED API service — HTTP client, retry, 429 handling, key injection.
src/services/canvas-bridge DataCanvas adapter — table naming, TTL/provenance tracking, SQL gate extras.
tests/ Unit and integration tests mirroring src/.
docs/ Design and planning documents.

Development guide

See CLAUDE.md for development guidelines and architectural rules. The short version:

  • Handlers throw, framework catches — no try/catch in tool logic
  • Use ctx.log for request-scoped logging, ctx.state for tenant-scoped storage
  • Register new tools in src/mcp-server/tools/definitions/index.ts
  • Wrap FRED API calls: validate raw response → normalize to domain type → return output schema; never fabricate missing fields

Contributing

Issues and pull requests are welcome. Run checks and tests before submitting:

bun run devcheck
bun run test

License

Apache-2.0 — see LICENSE for details.

from github.com/cyanheads/federal-reserve-mcp-server

Установка @Cyanheads/Federal Reserve Server

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/cyanheads/federal-reserve-mcp-server

FAQ

@Cyanheads/Federal Reserve Server MCP бесплатный?

Да, @Cyanheads/Federal Reserve Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для @Cyanheads/Federal Reserve Server?

Нет, @Cyanheads/Federal Reserve Server работает без API-ключей и переменных окружения.

@Cyanheads/Federal Reserve Server — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить @Cyanheads/Federal Reserve Server в Claude Desktop, Claude Code или Cursor?

Открой @Cyanheads/Federal Reserve Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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