MCP server

Isoba — Dollar & Crisis Index

io.github.nickarstrong/isoba

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

US dollar index, crisis meter, recession and market-top risk from public-domain data since 1990.

Website

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

8

Token cost

About 1,830 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http isoba https://isoba.lokio.org/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.isoba]
url = "https://isoba.lokio.org/mcp"

Gemini CLI

{"mcpServers":{"isoba":{"httpUrl":"https://isoba.lokio.org/mcp"}}}

Cursor

{"mcpServers":{"isoba":{"url":"https://isoba.lokio.org/mcp"}}}

VS Code

{"servers":{"isoba":{"type":"http","url":"https://isoba.lokio.org/mcp"}}}

Antigravity

agy mcp add isoba https://isoba.lokio.org/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"isoba","server_url":"https://isoba.lokio.org/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"isoba","server_url":"https://isoba.lokio.org/mcp"}

Tools

• find_similar_days ~209 tokens
  Days since 1990 when the 14 sensors of the crisis meter, market-top risk and recession risk stood closest to a given day (default: today), at least half a year apart and at least a year before the given day, and what followed within 12 months: the crisis meter peak, a US recession (NBER), an S&P 500
• get_changes_since ~177 tokens
  What moved between two dates and why: each instrument (from → to, zone change), the sensors that moved most and any that switched on or off, and the filters. Use when the user asked before ("since last week / since I last checked") or asks why a reading changed.
• get_current_readings ~268 tokens
  Today's readings with the data date: Dollar System Index (where the dollar system stands and what it is made of), Crisis meter (stress already present in credit and funding, four sensors with week-ago and month-ago values), market-top risk and US recession risk (how often an S&P 500 bear market or a
• get_expectations ~348 tokens
  What markets price now (Fed rate path from the 2-year Treasury yield, 5-year breakeven inflation, yields) and what happened over the next 12 months after the 10 days since 1990 most similar to today (same 14 sensors as find_similar_days, at least half a year apart), with the number of distinct cycle
• get_monthly_history ~282 tokens
  Monthly averages of one or several instruments between two months (DSI since 2006, the others since 1990), with the zone of each month. Use for trends and to see what the instruments showed around past events.
• get_readings_on_date ~167 tokens
  What Isoba showed on any working day since 1990-01-01: the four instruments with zones, every sensor, the eight filters (since 2006), the yield curve and the four credit inputs — computed point-in-time from data published by that day. Use for "what did it show before 2008 / on the day of COVID?".
• get_track_record ~282 tokens
  How Isoba behaved when run point-in-time over every working day since 1990 (only data published by each day, checked for look-ahead). Default section "summary" is short; ask for a section (crisis_events, recessions, market_tops, false_alarms, by_year, methods, all) or one event (gulf, ltcm, dotcom,
• what_to_watch ~97 tokens
  How many points each instrument is from the next zone boundary up or down, which sensors are closest to switching on or off (threshold 80), and the freshest and stalest inputs. Use for "what would change the picture?".

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