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@cyanheads/treasury-fiscaldata-mcp-server

by cyanheads

Version License Docker MCP SDK npm TypeScript Bun

Install in Claude Desktop Install in Cursor Install in VS Code

Framework

Public Hosted Server: https://treasury-fiscaldata.caseyjhand.com/mcp


Overview

US Treasury Fiscal Data — national debt, interest rates, exchange rates, and other fiscal datasets. Browse a curated catalog of 17 endpoints, query any endpoint directly, or stage large pulls as DuckDB dataframes for SQL analysis, from any MCP client. Runs as a stdio process, a local Streamable HTTP server, or the public hosted endpoint above.

Tools

Tool

Description

treasury_list_datasets

Browse the curated catalog of 17 Treasury Fiscal Data endpoints with field names, descriptions, and update cadence

treasury_query_dataset

Query any Treasury Fiscal Data endpoint by path, field list, filters, sort, and page — with optional DataCanvas spill

treasury_get_debt

Fetch national debt (Debt to the Penny) — latest record, specific date, or date-range series with optional DataCanvas spill

treasury_get_interest_rates

Average interest rates Treasury pays on outstanding securities by type — marketable issues, non-marketable series, and aggregate totals

treasury_get_exchange_rates

Official Treasury statutory exchange rates for ~165 countries, published quarterly

treasury_dataframe_describe

List DataCanvas dataframes materialized by the treasury_* tools with schema, row count, and TTL

treasury_dataframe_query

Run a single-statement SELECT against DataCanvas dataframes using standard DuckDB SQL

Related MCP server: @cyanheads/eia-energy-mcp-server

Capability reference

treasury_list_datasets tool

  • Filter by category: debt, interest_rates, exchange_rates, revenue_spending, savings_bonds, securities, other

  • Keyword search against dataset name and description (case-insensitive substring)

  • No network calls — serves from a static catalog bundled with the server

  • Returns endpoint paths, field names, types, and update cadence

  • Every path and field name is checked against the live API by bun run verify:catalog, so a dataset Treasury moves or renames fails a gate rather than reaching a caller


treasury_query_dataset tool

  • Filter syntax: { field, operator, value } with operator eq, gt, gte, lt, lte, in; multiple filters ANDed together

  • Pagination via page_size (1–10000, default 100) and page_number; sort any field, descending with a - prefix

  • All response values are strings per the API contract — including numeric and date fields; "null" means no value

  • Typed error reasons: invalid_endpoint, invalid_field, invalid_filter, page_out_of_range

  • canvas_id stages the page as a DataCanvas table (df_XXXXX_XXXXX) — read its schema with treasury_dataframe_describe, then SQL it with treasury_dataframe_query (requires CANVAS_PROVIDER_TYPE=duckdb)


treasury_get_debt tool

  • mode=latest — most recent business-day record; mode=date — a specific business day (YYYY-MM-DD; the API only records debt on market-open days); mode=series — a date range, newest-first

  • Records go back to 1993-04-01

  • mode=series auto-stages to a DataCanvas table when the range exceeds 500 rows, or on request via canvas_id; paging stops at 50,000 rows, with the response naming how many of the match were retrieved

  • Series rows returned inline are capped at 20, newest first — the full retrieved set is reachable via canvas_id

  • no_data_for_date error when no record exists for a requested date


treasury_get_interest_rates tool

  • mode=latest — most recent month's rates for all or one security type; mode=series — a time-range history

  • Covers every security type Treasury reports — marketable issues, non-marketable series, and aggregate totals; which types are published changes over time, so a security_type filter that matches nothing gets back the types the most recent month actually holds

  • Rates are percentages (e.g. "3.696"), not basis points

  • mode=series auto-stages to DataCanvas when results exceed 200 rows, or on request via canvas_id; inline series preview is capped at 20 rows, newest first


treasury_get_exchange_rates tool

  • Rate is foreign currency units per 1 USD (a Japan-Yen rate of 159.41 means 1 USD = 159.41 JPY) — official statutory reporting rates, not market rates

  • Published quarterly (Mar 31, Jun 30, Sep 30, Dec 31); filter to one or more countries by exact name, or omit for all ~165

  • mode=latest collapses to one row per currency — newest record_date, then newest effective_date — so an amendment supersedes the rate it replaced and a country with two legal tenders keeps both; mixed_record_dates flags a result whose rows span more than one quarter

  • mode=series auto-stages to DataCanvas when results exceed 500 rows; full published history is ~19,000 rows back to 2001-03-31, well within the 50,000-row paging cap

  • country_not_found error when a requested country has no records


treasury_dataframe_describe tool

  • Lists every active DataCanvas dataframe for the tenant, or one by name — source tool, query params, created/expiry timestamps, row count, and column schema

  • Requires CANVAS_PROVIDER_TYPE=duckdb; canvas_unavailable error otherwise

  • Columns show name, DuckDB type, and nullability — all Treasury columns are VARCHAR

  • truncated / max_rows flag when the source pull was capped before full materialization

  • Per-table TTL is sliding, touched on every dataframe op — default 24h, override with CANVAS_TTL_MS


treasury_dataframe_query tool

  • Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected; system catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied

  • All Treasury dataframe columns are VARCHAR — CAST to DECIMAL or DATE for arithmetic and date comparisons

  • row_limit caps rows produced (default 1000, max 10000); preview bounds the inline response and may not exceed row_limit

  • register_as persists the result as a new dataframe with a fresh TTL, for chained multi-step analysis

  • Typed error reasons: canvas_unavailable, system_catalog_access, invalid_sql, missing_table, invalid_query_bounds

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.

Fiscal Data-specific:

  • Curated catalog of 17 endpoints with field metadata — no discovery round-trip required; pass any endpoint path directly to treasury_query_dataset for datasets outside the catalog

  • Convenience tools for the three most-queried datasets — national debt, interest rates, exchange rates

  • DataCanvas integration: large pulls register as df_<id> dataframes queryable via DuckDB SQL, with automatic staging thresholds per tool

  • No API key required — the US Treasury Fiscal Data API is free and public

Agent-friendly output:

  • Provenance: filter-expression echo (applied_filters) and field-label maps (field_labels) let agents verify what was sent and read raw field names

  • Enrichment notices: empty-result guidance, partial-country mismatches, canvas staging confirmations, and truncated-series warnings all name the next tool call

  • Graceful truncation: series and query results carry truncated / retrieved_records / row_count_capped fields instead of silently dropping rows

  • Canvas provenance: source tool, original query parameters, row count, and column schema surfaced by treasury_dataframe_describe

Getting started

Public Hosted Instance

A public instance is available at https://treasury-fiscaldata.caseyjhand.com/mcp — no installation required. Point any MCP client at it via Streamable HTTP:

{
  "mcpServers": {
    "treasury-fiscaldata-mcp-server": {
      "type": "streamable-http",
      "url": "https://treasury-fiscaldata.caseyjhand.com/mcp"
    }
  }
}

Self-Hosted / Local

Add the following to your MCP client configuration file.

{
  "mcpServers": {
    "treasury-fiscaldata-mcp-server": {
      "type": "stdio",
      "command": "bunx",
      "args": ["@cyanheads/treasury-fiscaldata-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info"
      }
    }
  }
}

Or with npx (no Bun required):

{
  "mcpServers": {
    "treasury-fiscaldata-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cyanheads/treasury-fiscaldata-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info"
      }
    }
  }
}

Or with Docker:

{
  "mcpServers": {
    "treasury-fiscaldata-mcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "MCP_TRANSPORT_TYPE=stdio",
        "ghcr.io/cyanheads/treasury-fiscaldata-mcp-server:latest"
      ]
    }
  }
}

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

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

DataCanvas SQL workflow

For large time-series pulls or multi-dataset analysis, use the DataCanvas SQL workflow:

  1. Set CANVAS_PROVIDER_TYPE=duckdb in your server environment.

  2. Call a data tool with a canvas_id — e.g., treasury_get_debt with mode=series and a canvas_id value, or treasury_query_dataset with canvas_id. The tool registers the results as a df_XXXXX_XXXXX dataframe and returns the table name.

  3. Inspect the schema with treasury_dataframe_describe — lists column names, types (all VARCHAR for Treasury data), row count, and TTL.

  4. Query with SQL via treasury_dataframe_query — standard DuckDB SELECT with joins, aggregates, window functions, and CTEs. CAST VARCHAR columns to DECIMAL or DATE for arithmetic.

-- Example: debt trend over the last year, month-end records only
SELECT
  record_date,
  CAST(tot_pub_debt_out_amt AS DECIMAL) / 1e12 AS total_debt_trillions
FROM df_xxxxx
WHERE CAST(record_date AS DATE) >= CURRENT_DATE - INTERVAL 1 YEAR
ORDER BY record_date DESC

Prerequisites

  • Bun v1.3.0 or higher (or Node.js v24+).

  • No API key required — the US Treasury Fiscal Data API is free and public.

  • For DataCanvas SQL: CANVAS_PROVIDER_TYPE=duckdb (DuckDB is bundled as @duckdb/node-api).

Installation

  1. Clone the repository:

git clone https://github.com/cyanheads/treasury-fiscaldata-mcp-server.git
  1. Navigate into the directory:

cd treasury-fiscaldata-mcp-server
  1. Install dependencies:

bun install
  1. Configure environment:

cp .env.example .env
# edit .env as needed — no required vars; CANVAS_PROVIDER_TYPE=duckdb to enable SQL

Configuration

Variable

Description

Default

CANVAS_PROVIDER_TYPE

Canvas engine. Unset resolves to none, and the treasury_dataframe_* tools then reject every call — set it to duckdb to enable DataCanvas SQL.

none

CANVAS_TTL_MS

Per-table TTL for DataCanvas dataframes in milliseconds.

86400000 (24h)

MCP_TRANSPORT_TYPE

Transport: stdio or http.

stdio

MCP_HTTP_PORT

Port for HTTP server.

3010

MCP_SESSION_MODE

HTTP session handling: auto, stateful, or stateless. Setting it overrides the server's own declaration; leaving it unset falls through to that declaration, not to the schema default.

stateless (declared in src/index.ts)

MCP_AUTH_MODE

Auth mode: none, jwt, or oauth.

none

MCP_LOG_LEVEL

Log level (debug, info, notice, warning, error).

info

LOGS_DIR

Directory for log files (Node.js/Bun only).

<project-root>/logs

OTEL_ENABLED

Enable OpenTelemetry spans and metrics.

false

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

Running the server

Local development

  • Build and run:

    bun run rebuild
    
    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
    bun run verify:catalog   # Probe every catalog endpoint and field against the live API

    verify:catalog is the one check that needs the network, which is why it is separate from devcheck and the test suite. Run it after editing src/services/fiscal-data/datasets.ts and before a release.

Docker

docker build -t treasury-fiscaldata-mcp-server .
docker run --rm -e CANVAS_PROVIDER_TYPE=duckdb -p 3010:3010 treasury-fiscaldata-mcp-server

The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/treasury-fiscaldata-mcp-server. DuckDB native modules are pre-built in the build stage and copied to the production stage — no extra build tools required at runtime. 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/definitions/

Tool definitions (*.tool.ts) — 5 data tools + 2 DataCanvas tools.

src/services/fiscal-data/

Treasury Fiscal Data API client, embedded endpoint catalog, and types.

src/services/canvas-bridge/

Adapter over the framework DataCanvas: df_<id> minting, per-table TTL, system-catalog SQL deny.

tests/

Unit and integration tests mirroring src/.

Development guide

See CLAUDE.md and AGENTS.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

  • All Treasury API values are strings — validate and CAST in downstream SQL; never fabricate missing fields

  • Register new tools via the arrays in src/index.ts

Contributing

Issues are welcome. Run checks and tests before submitting:

bun run devcheck
bun run test

License

Apache-2.0 — see LICENSE for details.

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