federal-reserve-mcp-server

---

Overview

Economic data from FRED, the St. Louis Fed's database of ~800K time series on output, prices, employment, money, rates, housing, and trade. Search series, pull observations, browse categories and releases, and run SQL over large results.

Tools

Tool	Description
fedreserve_search_series	Full-text search across FRED series titles, tags, and notes
fedreserve_get_series	Fetch metadata for one or more series — title, units, frequency, observation range
fedreserve_get_observations	Fetch date+value observations for one or more series, with date-range and unit-transform filtering
fedreserve_browse_categories	Navigate the FRED category tree
fedreserve_get_release	Look up a FRED release by ID or name search, with its associated series
fedreserve_dataframe_describe	List active DataCanvas dataframes with provenance, schema, and row count
fedreserve_dataframe_query	Run a SELECT against registered DataCanvas dataframes via DuckDB SQL
fedreserve_dataframe_drop	Drop a DataCanvas dataframe by name (opt-in)

Capability reference

fedreserve_search_series _tool

• Full-text or series-ID search, with frequency, units, seasonal_adjustment, and tag_names filters; filter_variable and filter_value must be supplied together or the call returns invalid_filter
• Pagination via limit (default and max 1000) and offset (max 4999; FRED caps searchable results at 5000)
• Output includes active_filters and popularity (0–100) when available; empty results suggest a broader query or category browsing

---

fedreserve_get_series _tool

• Accepts one series ID or up to 50 per call
• Returns title, units, frequency, seasonal adjustment, observation range, popularity, and notes per series
• Failed IDs in a batch land in a failed array with error messages; a single unresolved ID throws series_not_found

---

fedreserve_get_observations _tool

• Accepts one series ID or up to 10, with observation_start / observation_end (YYYY-MM-DD), native unit transforms, and frequency downsampling via aggregation_method (avg, sum, eop)
• Returns date/value observations (values are strings that keep trailing zeros) plus per-series failures
• Multi-series or >500-row results go to a DataCanvas table with a 20-row preview; the notice names dataset.name and the fedreserve_dataframe_describe and fedreserve_dataframe_query calls to run next. Without canvas, you get a truncated inline preview

---

fedreserve_browse_categories _tool

• Omit category_id to start at the root (ID 0); returns the category and its children, or up to 10 sample series for a leaf
• An unknown category_id throws category_not_found

---

fedreserve_get_release _tool

• Takes exactly one of release_id or release_search (case-insensitive name substring)
• Returns release name, link, notes, the next five scheduled dates, and a paginated series list (series_limit max 1000, series_offset)
• An ambiguous name returns up to 10 search_alternatives; retry with the exact release_id

---

fedreserve_dataframe_describe _tool

• Lists active DataCanvas dataframes, newest first, or one by name
• Each entry carries source_tool, query_params, created_at, expires_at, row_count, truncated / max_rows, and column_schema

---

fedreserve_dataframe_query _tool

• Runs one read-only DuckDB SELECT against df_<id> tables (joins, aggregates, window functions, CTEs); external files, system catalogs, and engine-setting functions are blocked
• row_limit caps returned rows (default 1000, max 10000) and preview sets the inline sample; BIGINT results serialize as strings
• register_as saves the result as a new dataframe with its own TTL

---

fedreserve_dataframe_drop _tool

• Opt-in: enabled by FRED_DATAFRAME_DROP_ENABLED=true, otherwise registered as disabled
• Drops the named dataframe early; returns dropped: false when it doesn't exist

Features

Built on @cyanheads/mcp-ts-core: stdio and Streamable HTTP transports, pluggable auth (none / jwt / oauth), swappable storage (in-memory, filesystem, Supabase, Cloudflare KV/R2/D1), structured logging with optional OpenTelemetry tracing.

FRED-specific:

• Requires a FRED_API_KEY for the FRED API (up to 120 requests/minute)
• Unit transforms and frequency downsampling run on FRED's side against the full series history
• Large observation results spill to DataCanvas tables you can query with SQL
• Dataframe tools require CANVAS_PROVIDER_TYPE=duckdb and report canvas_unavailable otherwise

Agent-friendly output:

• Partial failures: fedreserve_get_series and fedreserve_get_observations return per-ID failed rows instead of failing the whole request
• Ambiguous release names return search_alternatives instead of a guess
• Every dataframe carries source_tool, query_params, and TTL fields
• Without DataCanvas, fedreserve_get_observations returns a truncated inline preview with an explanatory message

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

• Bun v1.4.0 or higher (or Node.js v24+).
• A free FRED API key from stlouisfed.org. The key grants 120 requests/minute.

Installation

1. Clone the repository:

git clone https://github.com/cyanheads/federal-reserve-mcp-server.git

2. Navigate into the directory:

cd federal-reserve-mcp-server

3. Install dependencies:

bun install

4. 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	TTL for DataCanvas observation tables, in seconds.	86400
FRED_DATAFRAME_DROP_ENABLED	Set true to enable fedreserve_dataframe_drop; otherwise registered as disabled.	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_SESSION_MODE	HTTP session mode: auto, stateful, or stateless.	stateless
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
OTEL_EXPORTER_OTLP_ENDPOINT	Base OTLP URL for traces (/v1/traces) and metrics (/v1/metrics).	—
OTEL_EXPORTER_OTLP_LOGS_ENDPOINT	OTLP log endpoint (logs are off unless set).	—
LOG_TOOL_FAILURE_PAYLOADS	Log failed tool arguments and results with key-name redaction; secrets in free-form values are not redacted.	false
LOG_TOOL_FAILURE_PAYLOAD_MAX_BYTES	Byte cap per logged payload.	16384

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

Set CANVAS_PROVIDER_TYPE=duckdb to enable SQL over observation tables. npm installs and Docker images include the DuckDB runtime. Portable Claude Desktop bundles omit native bindings; use the npm or Docker installation for canvas mode.

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 are welcome. Run checks and tests before submitting:

bun run devcheck
bun run test

License

Apache-2.0 — see LICENSE for details.