MCP server

Project Gumball

com.gumballtools/platform

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

One MCP server exposing every tool in the Gumball portfolio.

Website Source

At a glance

Type

MCP server

Publisher

gumballtools.com (verified by the MCP Registry)

Status

Working at last check

Tools

25

Token cost

About 11,193 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 platform https://gumballtools.com/api/mcp

Claude Desktop

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

Codex (config.toml)

[mcp_servers.platform]
url = "https://gumballtools.com/api/mcp"

Gemini CLI

{"mcpServers":{"platform":{"httpUrl":"https://gumballtools.com/api/mcp"}}}

Cursor

{"mcpServers":{"platform":{"url":"https://gumballtools.com/api/mcp"}}}

VS Code

{"servers":{"platform":{"type":"http","url":"https://gumballtools.com/api/mcp"}}}

Antigravity

agy mcp add platform https://gumballtools.com/api/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":"platform","server_url":"https://gumballtools.com/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"platform","server_url":"https://gumballtools.com/api/mcp"}

Tools

• amortize_schedule ~639 tokens
  Returns the full row-by-row schedule: per-period interest, scheduled principal, any extra principal, PMI, payment and running balance. Handles monthly or daily accrual (daily needs a start date, so leap years follow from the calendar rather than an assumption), biweekly payments, one-off or recurrin
• body_metrics ~514 tokens
  Compute BMI, energy expenditure, and protein targets from height and weight. Height and weight MUST carry units — a bare number is REFUSED rather than guessed, because a unit mix-up produces a plausible-looking answer that is badly wrong. Returns every standard BMR formula plus the spread between th
• check_digit_run ~477 tokens
  Checks the check digit on an IBAN (ISO 7064 MOD 97-10), ISBN-10, ISBN-13, EAN-13, UPC-A, or a Luhn-checked card number. When the checksum fails it searches for the single substitution or adjacent transposition that would repair it, so the answer is which character to fix rather than merely that some
• color_analyse ~298 tokens
  Convert a colour between hex, RGB, HSL, OKLCH, CMYK, and CSS names, and derive complementary, analogous, triadic, split-complementary and monochromatic harmonies. Harmonies are rotated in OKLCH, not HSL, so they keep their perceived lightness instead of one looking washed out. Reports WCAG contrast
• cron_build ~247 tokens
  Convert an English schedule description into a cron expression. Rule-based, not a language model: it refuses phrases outside its grammar rather than guessing, and reports which words it did not use so you can tell whether it read you correctly. WHY DELEGATE THIS: Cron has counter-intuitive rules: d
• cron_explain ~340 tokens
  Translate a cron expression into plain English, list upcoming run times in a timezone, and report the gotchas that make schedules misfire: day-of-month/day-of-week OR semantics, steps that do not divide evenly, impossible dates, and daylight-saving shifts. Prefer this over reasoning about the expres
• cron_next_runs ~442 tokens
  Lists the next run times for a cron expression in a specific timezone, with no prose. Use it when the only question is "when does this next fire" — whether a job runs before a deadline, or what a user's upcoming schedule looks like. Do not compute these dates unaided: weekday arithmetic, month lengt
• due_date ~573 tokens
  Estimate a due date from a last menstrual period, a known conception date, an IVF transfer, or an ultrasound measurement. Gestational age is counted from the LAST PERIOD, not conception: at "6 weeks pregnant" conception was about 4 weeks ago. Applies the cycle-length adjustment most calculators skip
• equation_steps_run ~479 tokens
  Solves a linear or quadratic equation in one variable and returns every step: expanding parentheses, combining like terms, moving terms across the equals sign, and applying the quadratic formula with the discriminant stated. Reports identities and contradictions as such rather than as "no answer", g
• iso_week_run ~679 tokens
  Converts calendar dates to ISO 8601 week-numbering dates and back, in either direction, and reports how many weeks an ISO year has. Use it whenever a date must be expressed as a week number or a week number turned back into a date — sprint planning, reporting periods, "week 37" scheduling, or recon
• json_to_types ~296 tokens
  Convert a JSON sample into TypeScript interfaces and a matching Zod schema. Merges EVERY array element into a union rather than typing from the first, keeps optional and nullable distinct, and emits unknown with a warning for empty containers instead of inventing a shape. Read the warnings before tr
• offside ~672 tokens
  Returns a verdict plus every step taken. THREE verdicts, not two: offside, onside, and no-offside-offence — the last is real and common, because in soccer an offside POSITION is not an offence without involvement in active play. Soccer: hands and arms never count (boundary at the bottom of the armpi
• offside_rule_contrast ~363 tokens
  Returns the structural differences between soccer offside and hockey offside, one dimension at a time. Use it when someone asks how the two compare, and — more usefully — before reasoning about one sport using an intuition from the other, which is the commonest way to get either wrong. They differ
• price_band ~555 tokens
  For a list price and a tax rate, finds every nearby list price that settles to the SAME cash total, and the highest one. Use it for "what should I charge" and "can I price to gain from rounding" questions. There is exactly one free move here and it is easy to get backwards, which is why this is wor
• regex_explain ~293 tokens
  Explain a regular expression in plain English and detect catastrophic backtracking. ALWAYS call this before putting a pattern where it will run against untrusted input: (a+)+$ looks harmless and takes minutes of CPU on a failing 30-character input. Also flags missing anchors, unescaped dots, ranges
• round_cash_total ~438 tokens
  Settle a transaction: exact subtotal, tax computed on that exact subtotal, then round the final total to the nearest nickel — and ONLY for cash. Card, EFT and gift-card payments stay priced to the cent, so the same basket legitimately comes to two amounts. Rounding applies to the TOTAL, never per it
• rounding_impact ~335 tokens
  Compute the mean rounding delta per cash transaction across a price list. Answers "does rounding make retailers money" with arithmetic rather than a guess: symmetric rounding nets to essentially zero by construction. Pass always-up to quantify the "just round everything up" idea, which is worth abou
• timezone_convert ~371 tokens
  Convert a wall-clock time between IANA zones. Returns null when the local time DOES NOT EXIST because a daylight-saving jump skipped it, and both candidates when it happens twice. Rejects ambiguous abbreviations — most runtimes accept "BST" and silently resolve it to Bangladesh (UTC+6) when nearly e
• validate_auto ~508 tokens
  Detects whether a payload is JSON, YAML, XML or CSV, then validates it. Use it for a file with no extension, a clipboard paste, or a response body with an unhelpful content type. Detection is structural and the reason is always returned, so the assumption is visible: a leading "<" is XML, "{" or "["
• validate_csv ~586 tokens
  Validates CSV against RFC 4180 and reports ragged rows individually with both field counts, because "row 4813 has 6 fields, the header has 5" is the entire answer. A ragged row loads without complaint almost everywhere — pandas pads or throws by engine, Excel shifts the columns, split(",") mis-assig
• validate_json ~498 tokens
  Validates a JSON document and reports every problem in one pass with a 1-based line and column, a stable rule code and a fix hint. Reports the three things JSON.parse cannot: duplicate keys (accepted by every parser, which then disagree about which value wins), integer precision loss past 2^53-1 pro
• validate_xml ~488 tokens
  Validates XML for well-formedness, namespace correctness and entity-based attacks. Catches four classes of invalid XML that ordinary well-formedness checkers accept: two root elements, undeclared namespace prefixes (well-formed as raw XML and rejected by XPath, XSLT, SOAP and every schema validator)
• validate_yaml ~484 tokens
  Validates a YAML document, including the values that mean different things to different loaders — found by resolving each unquoted scalar under both spec versions and comparing, not by matching a list of words. In YAML 1.1 (PyYAML) the bare words no/yes/on/off/y/n are booleans, so a country list los
• vocab_check ~281 tokens
  Mark an attempt and get the teaching content: whether it was right, which option was correct, why it fits, and why EVERY distractor fails. Read the distractor reasons out even when the learner was right — knowing why the tempting option was tempting is the part that transfers. WHY DELEGATE THIS: A
• vocab_draw ~337 tokens
  Draw words-in-context practice questions from a curated bank. The response deliberately contains NO answers and NO explanations, so you can quiz someone without leaking them — call vocab_check for the answer and the reason each distractor fails. Pass a seed to make a set reproducible. WHY DELEGATE

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