@cyanheads/federal-reserve-mcp-server
by cyanheads
README.md
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<h1>@cyanheads/federal-reserve-mcp-server</h1>
<p><b>Search and fetch ~800K Federal Reserve economic time-series from the FRED API via MCP. STDIO or Streamable HTTP.</b>
<div>8 Tools</div>
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---
## 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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` <sub>tool</sub>
- 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`](https://github.com/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](https://research.stlouisfed.org/docs/api/api_key.html).
```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):
```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:
```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 v1.4.0](https://bun.sh/) or higher (or Node.js v24+).
- A free FRED API key from [stlouisfed.org](https://fredaccount.stlouisfed.org/login/secure/). The key grants 120 requests/minute.
### Installation
1. **Clone the repository:**
```sh
git clone https://github.com/cyanheads/federal-reserve-mcp-server.git
```
2. **Navigate into the directory:**
```sh
cd federal-reserve-mcp-server
```
3. **Install dependencies:**
```sh
bun install
```
4. **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`.
| Variable | Description | Default |
|:---------|:------------|:--------|
| `FRED_API_KEY` | **Required.** API key from [stlouisfed.org](https://research.stlouisfed.org/docs/api/api_key.html). | — |
| `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](https://github.com/cyanheads/mcp-ts-core/tree/main/docs/telemetry). | `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`](./.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:**
```sh
# One-time build
bun run rebuild
# Run the built server
bun run start:stdio
# or
bun run start:http
```
- **Run checks and tests:**
```sh
bun run devcheck # Lint, format, typecheck, security
bun run test # Vitest test suite
bun run lint:mcp # Validate MCP definitions against spec
```
### Docker
```sh
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`](./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:
```sh
bun run devcheck
bun run test
```
## License
Apache-2.0 — see [LICENSE](LICENSE) for details.
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