Euclid

> _"What is asserted without proof can be dismissed without proof, but what is proved, endures."_ > In the spirit of Euclid of Alexandria Twenty-three centuries ago, Euclid of Alexandria looked at the mathematics of his time, a tangle of folklore, intuition, and "trust me", and said: _no more_. He built geometry from the ground up on axioms and proofs. If something was true, you could _show_ it was true. No hand-waving. No guessing. Large language models have the same problem Euclid's contemporaries did. They don't calculate. They _predict_. When you ask an LLM "what's 247 x 389?", it pattern-matches against its training data and guesses what the answer probably looks like. Sometimes right, sometimes wrong. You'd never know the difference. Deterministic computation tools for AI agents. Euclid is a hosted MCP server that gives any AI agent access to real, deterministic computation engines. What is self-evident should not be guessed, and arithmetic is about as self-evident as it gets. ---

Quick Start

Claude Code

``bash claude mcp add euclid --transport http https://mcp.euclidtools.com `

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows): `json { "mcpServers": { "euclid": { "url": "https://mcp.euclidtools.com" } } } `

Cursor

Add to .cursor/mcp.json in your project root (or ~/.cursor/mcp.json globally): `json { "mcpServers": { "euclid": { "url": "https://mcp.euclidtools.com" } } } `

Windsurf

Add to ~/.windsurf/mcp.json: `json { "mcpServers": { "euclid": { "url": "https://mcp.euclidtools.com" } } } `

VS Code (Copilot)

Add to .vscode/mcp.json in your project: `json { "servers": { "euclid": { "type": "http", "url": "https://mcp.euclidtools.com" } } } `

Other MCP Clients

Any MCP client that supports HTTP transport will work. Point it at: ` https://mcp.euclidtools.com ` Authentication is handled automatically via OAuth 2.1. Your client will prompt you to sign in on first connection. ---

Verify It Works

After connecting, ask your AI agent: > "What is 247 times 389?" If Euclid is working, the agent will call the calculate tool instead of predicting the answer. You'll see the tool call in the response. The correct answer is 96,083, and unlike mental math, it's guaranteed. ---

The Problem

LLMs are non-deterministic. Every token they produce is a _prediction_, including math: - 247 × 389 → the model _predicts_ 96,083 (sometimes it gets 96,183 or 95,983) - sin(47.3°) × cos(12.1°) → the model _predicts_ something close-ish - 15% of $8,472.50 → the model _predicts_ a dollar amount Sometimes the predictions are correct. Sometimes they're subtly wrong. The problem is you can never be sure which is which. Euclid makes this a non-issue. When an AI agent has Euclid available, it sends expressions to a real computation engine and returns the computed result. Deterministic. Correct. Every time. Think of it like what grep did for AI code search. A simple, proven tool that gives the model a capability it fundamentally lacks. ---

Why Not Just Use Code Execution?

Many LLM environments have code execution tools (Python sandboxes, etc.) that can do math. The difference: | | Code Execution | Euclid | | ------------------- | ---------------------------------- | ------------------------------------------ | | Overhead | Spins up a sandbox/interpreter | Near-zero: evaluates an expression string | | Latency | Hundreds of ms to seconds | Single-digit ms | | Availability | Varies by client | Any MCP client | | Model behavior | Model writes _code_ that does math | Model writes a _math expression_ | | Failure modes | Syntax errors, runtime exceptions | Clear error with hint and examples | | Token cost | Code generation is verbose | Expression strings are minimal | ---

Enforce Deterministic Computation

Installing Euclid gives your AI access to a calculator. But access alone isn't enough: the AI needs to be instructed to reach for it. Without an explicit directive, models will still predict math from training data by default. Add the following to your project's AI instruction file. Pre-built versions are in the rules/ directory: | File | For | |------|-----| | rules/CLAUDE.md | Claude Code | | rules/AGENTS.md | OpenAI Codex | | rules/.cursorrules | Cursor | | rules/.windsurfrules | Windsurf | The content is identical. Copy the one that matches your IDE into your project root, or append it to your existing instruction file. <details> <summary>Preview the instruction block</summary> `markdown

Deterministic Computation (Euclid)

NEVER predict, guess, or mentally compute numerical results. LLMs produce answers by pattern-matching against training data, sometimes right, sometimes subtly wrong, and there is no way to tell which. Always use Euclid's MCP tools instead. | Tool | When to Use | | ------------ | -------------------------------------------------------------------------------------------------------------------------------------- | | calculate | Arithmetic, percentages, margins, exponents, trig, logarithms, factorials. Any expression with a numerical answer | | convert | Unit conversions: m² to acres, km to miles, L/hr to gal/hr, °C to °F, bytes to kB, etc. | | statistics | Mean, median, mode, std deviation, variance, percentile, min, max, sum. Plus t-test, z-test, chi-squared, confidence intervals, correlation | | datetime | Date differences, add/subtract time, business days, age, day of week, quarter, leap year. Any calendar arithmetic | | encode | Base64, hex, URL, HTML encoding/decoding; SHA-256/512, SHA-1, MD5 hashing; HMAC signatures; JWT decoding | | finance | Loan payments, amortization, present/future value, NPV, IRR, CAGR, margin/markup, compound interest. Any financial formula | | regex | Pattern testing, text extraction, match-all, replace, split. Execute patterns, never predict whether they match | | color | Color conversion (hex, RGB, HSL, etc.), contrast ratios, WCAG accessibility, lighten/darken, palette generation | | validate | Email, URL, UUID, credit card (Luhn check), IPv4, IPv6, IBAN. Structural validation with check digits | | geo | Distances (Haversine/Vincenty), bearings, midpoints, destination points, polygon area, point-in-polygon, coordinate conversions | This applies everywhere, not just code. Analytics, business metrics, growth rates, marketing numbers, cost calculations, date arithmetic, financial projections during conversation. If there is a number to compute, a date to calculate, or data to encode, hash, or validate, use Euclid. No exceptions. ` </details> Why this matters: LLMs will confidently produce incorrect arithmetic with no indication anything is wrong. A model that returns 247 × 389 = 96,183 looks just as confident as one that returns the correct 96,083. The only way to guarantee correctness is to compute, not predict. ---

Tools

Euclid has 10 tools.

calculate

Evaluates mathematical expressions deterministically. ` calculate("(245 389) + (12^3 / 7)") → 95,551.857... calculate("sqrt(144)") → 12 calculate("sin(45 deg)") → 0.707... calculate("10!") → 3,628,800 calculate("e^(i pi) + 1") → 0 (Euler's identity) ` Supports: arithmetic, order of operations, exponents, roots, trigonometry, logarithms, factorials, constants (pi, e, phi), complex numbers, Unicode math symbols (×, ÷, √, π, ², ³).

convert

Converts between units deterministically. ` convert(100, "fahrenheit", "celsius") → 37.778 convert(5, "km", "miles") → 3.107 convert(1024, "bytes", "kB") → 1.024 convert(60, "mph", "km/h") → 96.561 ` Supports: length, mass, volume, temperature, area, speed, time, data, and 100+ units. Natural language aliases (e.g. "celsius", "miles per hour") are normalized automatically.

statistics

Statistical calculations, both descriptive and inferential. ` statistics("mean", [23, 45, 12, 67, 34]) → 36.2 statistics("std", [23, 45, 12, 67, 34]) → 21.159 statistics("z_test_proportion", { ... }) → { significant: true, p_value: 0.023 } statistics("confidence_interval", { data: [...] }) → { lower: 28.1, upper: 44.3 } ` Descriptive: mean, median, mode, std, variance, min, max, sum, percentile. Inferential: z-test, t-test, chi-squared, confidence intervals, correlation, normal CDF/inverse.

datetime

Deterministic date and time arithmetic. ` datetime("difference", { from: "2026-01-01", to: "2026-03-15", unit: "days" }) → 73 datetime("add", { date: "2026-01-01", amount: 90, unit: "days" }) → "2026-04-01" datetime("age", { birthDate: "1990-06-15", asOf: "2026-03-21" }) → 35 datetime("business_days", { from: "2026-01-01", to: "2026-01-31" }) → 22 ` 9 operations: difference, add, subtract, business_days, days_in_month, age, quarter, day_of_week, is_leap_year.

encode

Deterministic encoding, decoding, hashing, and JWT inspection. ` encode("base64_encode", { input: "hello world" }) → "aGVsbG8gd29ybGQ=" encode("sha256", { input: "hello world" }) → "b94d27b9..." encode("hmac", { input: "data", key: "secret", algorithm: "sha256" }) → "1b779..." encode("jwt_decode", { input: "eyJhbGci..." }) → { header, payload, signature } ` 16 operations: base64, base64url, hex, url, html (encode/decode), sha256, sha512, sha1, md5, hmac, jwt_decode.

finance

Financial calculations using arbitrary-precision decimal arithmetic. ` finance("loan_payment", { principal: 350000, rate: 6.5, periods: 360 }) → $2,212.24/mo finance("irr", { cashflows: [-100000, 30000, 35000, 40000, 45000] }) → 17.094% finance("compound_growth", { start_value: 2.1M, end_value: 4.8M, periods: 4 }) → 22.958% CAGR ` 16 operations: loan_payment, amortization, present_value, future_value, periods, interest_rate, npv, irr, roi, markup, margin, discount, percentage_change, compound_growth, simple_interest, compound_interest.

color

Color conversion, accessibility checks, and palette generation. ` color("convert", { color: "#FF6B35", to_space: "hsl" }) color("contrast_ratio", { foreground: "#FFFFFF", background: "#2563EB" }) → "4.62:1" color("wcag_level", { foreground: "#FFFFFF", background: "#2563EB" }) → "AA" color("analogous", { color: "#2563EB", count: 5 }) ` 14 operations across conversion, accessibility (WCAG), manipulation, and palette generation. 8 color spaces: hex, rgb, hsl, hsv, cmyk, lab, oklab, oklch.

regex

Safe regex execution (guaranteed linear-time, no ReDoS). ` regex("test", { pattern: "^\\d{3}-\\d{4}$", subject: "555-1234" }) → true regex("matchAll", { pattern: "\\d+", subject: "abc 123 def 456" }) → ["123", "456"] regex("replace", { pattern: "\\s+", subject: "a b c", replacement: " " }) → "a b c" ` 6 operations: test, match, matchAll, replace, split, escape.

validate

Structural validation with check digits. ` validate("email", { input: "[email protected]" }) → { valid: true } validate("credit_card", { input: "4111111111111111" }) → { valid: true, type: "Visa" } validate("iban", { input: "GB82WEST12345698765432" }) → { valid: true } ` Formats: email, url, uuid, credit_card (Luhn), ipv4, ipv6, iban.

geo

Geospatial calculations. ` geo("distance", { from: [lat, lon], to: [lat, lon] }) → km (Haversine or Vincenty) geo("bearing", { from: [lat, lon], to: [lat, lon] }) → degrees geo("point_in_polygon", { point: [lat, lon], polygon: [...] }) → true/false `` Distance, area, midpoint, bearing, destination point, point-in-polygon, coordinate conversions. ---

Pricing

Every account starts with 1,000 free tool calls. No credit card required. After that, top up credits at app.euclidtools.com. ---

Philosophy

Everything an LLM produces is a prediction. For creative writing and reasoning, that's fine. For math, it's a problem. The solution isn't to make models better at predicting math. It's to give them a calculator. This is part of a broader principle: wherever a model does something predictive that should be deterministic, give it a deterministic tool. Math is the most obvious case, but the same logic applies to unit conversions, date arithmetic, regex evaluation, encoding, and more. ---

License

The Euclid MCP server is proprietary software. This repository contains connection instructions, skills, and documentation for integration purposes. All rights reserved. See LICENSE for details. --- <p align="center"> <i>Euclid of Alexandria formalized mathematical proof 2,300 years ago.<br> We're just giving his tools to the machines.</i> </p>