Epoch

Name: Epoch
Author: KyaniteLabs

by KyaniteLabsversion 0.6.0i★ –iRuns on your computer

Registry nametech.kyanitelabs/epoch

Install

Overview

Description from the maker (original English)

Epoch time estimation MCP server for PERT, COCOMO, Monte Carlo, calibration, cost, and risk.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "epoch": {
      "command": "npx",
      "args": [
        "-y",
        "@kyanitelabs/epoch"
      ]
    }
  }
}

Run this in your terminal

claude mcp add epoch -- npx -y @kyanitelabs/epoch

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "epoch": {
      "command": "npx",
      "args": [
        "-y",
        "@kyanitelabs/epoch"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "epoch": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@kyanitelabs/epoch"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain kyanitelabs.tech (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32691 servers in this category
Published to the registry more recently than 77% of the other 32691 servers in this category
Basic checks equal to or better than 100% of the other 32691 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Epoch safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.6.0) reached the registry 10 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Dialyne

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Epoch -- Time Estimation MCP Server

Epoch is a time estimation MCP server that helps engineering leads, agents, and planners who need calibrated duration estimates produce PERT/reference-class estimates and record actuals.

TL;DR: Epoch — time estimation MCP server. Best for engineering leads, agents, and planners who need calibrated duration estimates.

Epoch helps AI agents understand time.

AI can write code, analyze data, and build apps -- but it can't tell you how long something will take, what it'll cost, or whether a deadline is realistic. Epoch fixes that.

Show Me

You: "How long will a 15,000 line project take with a small team?"

Claude (using Epoch): COCOMO II nominal: 100 person-months (traditional team) AI-adjusted: 9 person-months (LLM-assisted workflow) Schedule risk: medium (MAPE 15%, based on 28 historical features) Cost estimate (Claude Sonnet): ~$340 in API tokens

You: "How many working days between now and launch?"

Claude (using Epoch): Start: May 1, 2026 End: July 15, 2026 Business days: 54 Weekend days: 16 Holidays: 1 (Independence Day) Total calendar days: 75

You: "Which AI model should we use for a 50k-token job?"

Claude (using Epoch): gemini-2.0-flash: $0.02 -- fast, budget-friendly gpt-4o-mini: $0.02 -- fast, budget-friendly gemini-2.5-pro: $0.37 -- standard, high quality claude-sonnet-5: $0.57 -- standard, high quality Recommendation: gemini-2.0-flash for cost, claude-sonnet-5 for quality

Why Epoch?

Every AI agent hallucinates timelines. "This should take about 2 hours" becomes 2 days. Epoch gives AI grounded, data-driven estimates instead of guesses. It packages established estimation methods (PERT, COCOMO II, Monte Carlo, reference class forecasting) into 26 tools any AI can call -- so your assistant stops guessing and starts calculating.

Works out of the box. Epoch ships with a bundled reference database: task-type correction factors and scope baselines from the maintainer's recorded estimate-vs-actual history plus curated public research, and tool-usage/latency telemetry samples (117,791 across the bundled canary-test and session benchmarks) that keep the token-time bridge grounded. You get reasonable estimates from day one — no data collection or account setup required. If you choose to record your actuals, Epoch's self-improvement engine learns your patterns and gets even more precise over time.

What is MCP?

MCP (Model Context Protocol) is how AI assistants like Claude connect to external tools. Think of it like a plugin system -- you add Epoch with one command, and suddenly your AI assistant can estimate timelines, calculate business days, compare model costs, and predict whether your project will finish on time.

Quick Start

30-second setup -- works in Claude Code, Cursor, VS Code, and Windsurf:

claude mcp add epoch -- npx -y @kyanitelabs/epoch@0.7.0

That's it. Your AI assistant now has 26 time estimation tools.

Or add it to your project's .mcp.json:

"mcpServers": { "epoch": { "command": "npx", "args": ["-y", "@kyanitelabs/epoch@0.7.0"] } } }

Limit Epoch tools in Hermes

Use Hermes tools.include to expose only these example tools:

mcp_servers:

epoch: tools: { include: [pert_estimate, cocomo_estimate] }

Agent Skill

Epoch also ships a public agent skill at skills/epoch/SKILL.md. Use $epoch in compatible agent hosts when you want the agent to choose the right Epoch MCP or CLI workflow for time estimates, business-day math, model-cost comparison, schedule risk, and estimate-vs-actual feedback.

What Can Epoch Do?

What you want	What Epoch does	No jargon
"How long will this take?"	Gives you a realistic estimate with best/worst case ranges	Estimates
"Can we hit this deadline?"	Tells you if your timeline is realistic or risky	Schedule risk
"How much will the AI calls cost?"	Calculates token costs across 16 AI models side-by-side	Cost comparison
"How many business days between now and launch?"	Counts days excluding weekends and holidays (5 countries)	Calendar math
"Are our estimates getting better?"	Tracks your accuracy over time and auto-corrects	Self-improving
"What model should we use?"	Compares speed, cost, and quality across all major AI models	Model comparison

Technical Reference

Everything below is for developers who want to understand the internals, use the CLI or REST API, or contribute to Epoch.

Architecture

Six-layer design with 26 tools for time estimation, scheduling, cost analysis, and feedback:

Layer	Purpose	Tools
1. Core Temporal	Time, timezones, duration, date math	`get_current_time`, `convert_timezone`, `parse_duration`, `time_math`
2. Calendar Math	Business days, holidays (US/UK/FR/DE/JP)	`add_business_days`, `count_business_days`
3. Estimation	PERT, COCOMO II, sprint, CPM, Monte Carlo	`pert_estimate`, `cocomo_estimate`, `sprint_forecast`, `critical_path`, `monte_carlo_schedule`
4. Analytics	Reference class, context classification, calibration, token-time bridge, wait-mechanism deadlines	`reference_class_estimate`, `estimate_from_context`, `calibrate_estimates`, `token_time_bridge`, `wait_bound`
5. Cost & Risk	Token cost, model comparison, accuracy trends, risk, COCOMO validation	`token_cost_estimate`, `compare_models`, `accuracy_trend`, `schedule_risk`, `cocomo_validate`, `cocomo_ground_truth`
6. Feedback	Record actuals, track pending estimates, batch operations, health checks	`record_actual`, `get_pending_estimates`, `batch_record_actuals`, `feedback_health`

Tool Reference

Layer 1 -- Core Temporal

`get_current_time` -- Current wall-clock time in any IANA timezone

Input:  { timezone: "America/New_York" }

Output: { iso: "2026-05-01T08:30:00.000-04:00", humanReadable: "Fri, May 1, 2026, 8:30 AM EDT", timezone: "America/New_York", utcOffset: "-04:00" }

`convert_timezone` -- Convert a timestamp between IANA timezones

Input:  { timestamp: "2026-05-01T12:00:00Z", target_tz: "Asia/Tokyo" }

Output: { iso: "2026-05-01T21:00:00.000+09:00", timezone: "Asia/Tokyo", utcOffset: "+09:00", humanReadable: "Fri, May 1, 2026, 9:00 PM JST" }

`parse_duration` -- Parse human-readable duration strings

Input:  { duration_string: "2h30m" }

Output: { input: "2h30m", totalSeconds: 9000, humanReadable: "2 hours 30 minutes" }

`time_math` -- Date arithmetic operations

Input:  { operation: "add_days", operands: { start_date: "2026-05-01", days: 7 } }

Output: "2026-05-08"

Supported operations: add_days, add_business_days, diff, convert_tz, parse_nl, format_duration

Layer 2 -- Calendar Math

`add_business_days` -- Add N business days with holiday awareness (US, UK, FR, DE, JP)

Input:  { start_date: "2026-05-01", days: 5, country: "US" }

Output: { startDate: "2026-05-01", endDate: "2026-05-08", businessDays: 5, countryCode: "US", holidaySupport: "holiday_calendar", humanReadable: "5 business days from 2026-05-01 to 2026-05-08 (US)." }

`count_business_days` -- Count business days between two dates

Input:  { start_date: "2026-05-01", end_date: "2026-05-15", country: "US" }

Output: { startDate: "2026-05-01", endDate: "2026-05-15", businessDays: 10, countryCode: "US", holidaySupport: "holiday_calendar", humanReadable: "10 business days between 2026-05-01 and 2026-05-15 (US)." }

Both tools always include holidaySupport ("holiday_calendar" when the country has a bundled holiday set — US/UK/FR/DE/JP — otherwise "weekends_only") in successful output; country must match ^[A-Za-z]{2}$ — "USA"-style codes are rejected with a readable error.

Layer 3 -- Estimation

`pert_estimate` -- PERT three-point estimation with confidence intervals and urgency scoring

Input:  {

optimistic: 2, most_likely: 4, pessimistic: 12, unit: "hours" } Output: { expected: 5, variance: 2.78, stdDeviation: 1.67, confidence95: [1.67, 8.33], confidence99: [0, 10], unit: "hours", urgencyCategory: "medium", riskLevel: "high", humanReadable: "Expected 2.86–7.14 hours (80% confidence interval); point estimate 5 hours (ledger-recorded basis; adjustedEstimate 5 applies the correction factor). No task_type was supplied, so this interval is derived from the PERT variance (optimistic/most_likely/pessimistic spread) instead of empirical data.", developerProfile: { mode: "ai_native", correctionFactor: 1 }, adjustedEstimate: 5, rawEstimate: 5, correctionFactor: 1, n: 0, interval: { p50: { lower: 3.87, upper: 6.13 }, p80: { lower: 2.86, upper: 7.14 }, p90: { lower: 2.25, upper: 7.75 }, source: "pert_variance" }, intervalNote: "No task_type was supplied, so this interval is derived from the PERT variance (optimistic/most_likely/pessimistic spread) instead of empirical data.", basisNote: "Interval and point estimate are on the ledger-recorded basis (raw PERT expected × unit factor). adjustedEstimate (5 hours) additionally applies the correction factor (1) and is display-only — it is never recorded or calibrated against." }

(Example from a fresh install with no accumulated feedback; with ≥5 exclusion-filtered matched pairs for the task type, interval.source becomes "empirical_ratio_quantile", n reports the sample size, and intervalPopulation names the ratio population used.)

`cocomo_estimate` -- COCOMO II software sizing with LLM-adapted cost drivers

Input:  {

kloc: 15, reasoning_complexity: 1.2, context_completeness: 1.0, transformation_impact: 0.8, iterative_cycles: 1.5, human_oversight: 1.2 } Output: { kloc: 15, personMonthsNominal: 99.9, personMonthsLlmAdjusted: 8.9, effortMultipliers: { reasoning_complexity: 1.2, context_completeness: 1.0, transformation_impact: 0.8, iterative_cycles: 1.5, human_oversight: 1.2, product: 1.728 }, developerProfile: { mode: "ai_native", correctionFactor: 1.45 } }

LLM-adapted cost drivers include reasoning complexity, context completeness, transformation impact, iterative cycles, and human oversight requirements.

`sprint_forecast` -- Sprint velocity forecasting from historical data

Input:  {

backlog_points: 100, velocity_history: [20, 25, 22, 23], sprint_length_days: 14, hours_per_sprint: 80 } Output: { backlogPoints: 100, averageVelocity: 22.5, requiredSprints: 4.4, pessimisticSprints: 4.9, hoursPerPoint: 3.56, totalHours: 355.6, completionDays: 62, sprintLengthDays: 14, developerProfile: { mode: "ai_native", sprintVelocityPoints: 80, correctionFactor: 1.45 } }

`critical_path` -- Critical Path Method with merge-bias adjustment for parallel tasks

Input:  {

tasks: [ { name: "A", duration: 5, predecessor

Only the beginning is shown; read the rest in the repo

Epoch

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Dialyne

README from the maker

Epoch -- Time Estimation MCP Server

Show Me

Why Epoch?

What is MCP?

Quick Start

Limit Epoch tools in Hermes

Agent Skill

What Can Epoch Do?

Technical Reference

Architecture

Tool Reference

Layer 1 -- Core Temporal

Layer 2 -- Calendar Math

Layer 3 -- Estimation