GreenPick

Name: GreenPick
Author: bithug01

by bithug01version 0.6.2i★ –iRuns on your computer

Registry nameio.github.bithug01/greenpick

Install

Overview

Description from the maker (original English)

Greener, cheaper cloud infra decisions — carbon + cost + latency tradeoffs, in-editor.

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
You need to fill in: EIA_API_KEY, ENTSOE_TOKEN, ELECTRICITYMAPS_TOKEN

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).
You fill in yourself: GREENPICK_CARBON_SOURCE, EIA_API_KEY, ENTSOE_TOKEN, ELECTRICITYMAPS_TOKEN, GREENPICK_CACHE_TTL_SECONDS, GREENPICK_LOG_LEVEL

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx 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": {
    "greenpick": {
      "command": "uvx",
      "args": [
        "greenpick"
      ],
      "env": {
        "GREENPICK_CARBON_SOURCE": "your-value",
        "EIA_API_KEY": "your-value",
        "ENTSOE_TOKEN": "your-value",
        "ELECTRICITYMAPS_TOKEN": "your-value",
        "GREENPICK_CACHE_TTL_SECONDS": "your-value",
        "GREENPICK_LOG_LEVEL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add greenpick --env GREENPICK_CARBON_SOURCE=your-value --env EIA_API_KEY=your-value --env ENTSOE_TOKEN=your-value --env ELECTRICITYMAPS_TOKEN=your-value --env GREENPICK_CACHE_TTL_SECONDS=your-value --env GREENPICK_LOG_LEVEL=your-value -- uvx greenpick

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "greenpick": {
      "command": "uvx",
      "args": [
        "greenpick"
      ],
      "env": {
        "GREENPICK_CARBON_SOURCE": "your-value",
        "EIA_API_KEY": "your-value",
        "ENTSOE_TOKEN": "your-value",
        "ELECTRICITYMAPS_TOKEN": "your-value",
        "GREENPICK_CACHE_TTL_SECONDS": "your-value",
        "GREENPICK_LOG_LEVEL": "your-value"
      }
    }
  }
}

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": {
    "greenpick": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "greenpick"
      ],
      "env": {
        "GREENPICK_CARBON_SOURCE": "your-value",
        "EIA_API_KEY": "your-value",
        "ENTSOE_TOKEN": "your-value",
        "ELECTRICITYMAPS_TOKEN": "your-value",
        "GREENPICK_CACHE_TTL_SECONDS": "your-value",
        "GREENPICK_LOG_LEVEL": "your-value"
      }
    }
  }
}

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.

Values you fill in

GREENPICK_CARBON_SOURCE env
Carbon data source: 'auto' (US->EIA, EU->ENTSO-E, Canada->Hydro-Québec/IESO live), 'mock' (offline: typical monthly values from a year of real data), 'eia', 'entsoe', or 'electricitymaps'. Defaults t…
EIA_API_KEY secret env
Free US EIA-930 grid data API key (optional; enables live US carbon).
ENTSOE_TOKEN secret env
Free EU ENTSO-E grid data token (optional; enables live EU carbon + day-ahead forecast).
ELECTRICITYMAPS_TOKEN secret env
Electricity Maps API token (optional; used when GREENPICK_CARBON_SOURCE=electricitymaps).
GREENPICK_CACHE_TTL_SECONDS env
Cache lifetime for fetched grid data, in seconds.
GREENPICK_LOG_LEVEL env
Logging level (DEBUG, INFO, WARNING, ERROR).

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account bithug01, which owns the repo
… 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 32398 servers in this category
Published to the registry more recently than 99% of the other 32398 servers in this category
Basic checks equal to or better than 100% of the other 32398 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 GreenPick 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?

You need to fill in: EIA_API_KEY, ENTSOE_TOKEN, ELECTRICITYMAPS_TOKEN

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 (0.6.2) reached the registry today.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

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

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago

Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday

Install

AI Deprecations

by aideprecations.com

AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.

Runs in the cloudUpdated today

Install

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.

GreenPick

Write greener, cheaper cloud infrastructure — before you deploy.

A design-time sustainability co-pilot that runs as an MCP server inside your vibe-coding environment (Cursor / Claude Code / Kiro). Ask it where to deploy, when to run a job, or how to right-size — and it answers with an honest carbon + cost + latency tradeoff, in-editor, in seconds. (It responds when you ask; auto-nudging on infra-code changes is on the roadmap.)

Status: working — 19 tools. Live carbon for US (EIA-930), EU (ENTSO-E) and Canada (Hydro-Québec,

IESO — no key needed), cross-cloud cost

parity (Vantage-refreshed), per-axis R/Y/G ratings, carbon-aware scheduling + day-ahead forecast,

GPU-training and LLM-inference carbon, right-sizing, serving-pattern and data-locality/residency

checks — all shipped. Offline or without API keys, falls back to clearly-labelled *typical* values:

this month's average for each grid, from a year of real data.

*The same 40-GPU-hour training run emits ~0.6 kg CO₂ in Stockholm vs ~17.5 kg in Sydney — a ~28× difference from region choice alone (typical October grids; Sydney on Ember's 2025 national figure, a lower bound for its coal-heavier state grid). Ask GreenPick and it surfaces that (with the cost and latency tradeoff) while you're still in the editor, before you commit.*

▶ [See the 5-minute demo](docs/demo.md) — three scenarios with real tool output (training placement, the egress backfire, the forecast).

Features

🧮 **Right-sizing that cuts cost *and* carbon together** — the FinOps win with a carbon twin. The money saved is the reason to run it; the carbon comes free.
⏱ Carbon-aware scheduling — run deferrable jobs (ETL, batch, training) when the grid is cleanest, now or day-ahead. A decision you make for *every* recurring job.
⚡ GPU training & LLM inference carbon — estimate a run's footprint and the greener *where* + *when*; the size/placement choices that actually move the number.
🌍 Greener region picks — ranked by carbon, with the cost + latency tradeoff shown, not hidden.
🛡 Backfire guards — flags when a greener move loses to egress, or crosses a data-residency line.
🔌 Live US + EU grid data, with a realistic fallback built from a year of real data — no API keys required to start.

Why this exists
What it is / is NOT · How it differs
Scope
MCP tools
Data sources
Honest limitations
Quick start
FAQ
Contributing
License

Why this exists

The same web service emits very different CO₂ depending on which region it runs in, because electricity grids differ in carbon intensity. Existing tools either rank regions in the abstract, or measure carbon *after* you deploy. GreenPick does it at the moment you choose, and tells you what the greener choice *costs you* in latency and dollars — so you can accept or reject it with eyes open.

What it is / is NOT

IS: directional "greener choice" guidance for a developer picking a cloud region while building. Guidance, with tradeoffs stated.
IS NOT: audited carbon accounting, ESG/Scope-2 reporting, or a real-time scheduler. GreenPick does not claim GHG-Protocol or ISO compliance — that's what the paid data vendors (Electricity Maps, WattTime) provide. GreenPick is for *decisions*, not *disclosures*.

How it differs from what's out there

Measurement tools (Cloud Carbon Footprint, CodeCarbon, Kepler) report what you *already* emitted, *after* you deploy. GreenPick advises *before* — at the choice.
Cloud providers' own tools (AWS CCFT, Azure, Google's "Low CO₂" region labels) cover *one* cloud and show carbon alone. GreenPick is cross-cloud and weighs carbon against cost and latency so you see the tradeoff, not just a green badge.
CI/CD carbon tools act at merge time on a pipeline job. GreenPick works earlier, in the editor, across more decisions (scheduling, right-sizing, training/inference, egress & residency).
Grid-data SDKs (Electricity Maps, WattTime, GSF Carbon Aware SDK) are building blocks; GreenPick is the decision layer on top of that kind of data.

The combination — cross-cloud, carbon + cost + latency, at design time, in the editor, with backfire guards — is the part nothing else puts together.

Scope

Providers: AWS, GCP, Azure — 25 regions across the US, Europe, Canada, Asia and Australia.
Workloads: long-running web/API services, GPU training runs, and deferrable jobs (ETL / batch / backups) — placement and timing for each.
Carbon = grid carbon intensity by region (directional, point-in-time; live US + EU), plus a day-ahead forecast (EU) for forward-looking scheduling.
Cost = compute + egress ballpark (deterministic static table, apples-to-apples across clouds; never LLM-invented).
Latency = geographic estimate to a stated user location.
Efficiency levers: greener instance family (perf-per-watt), right-sizing (cost + carbon together), and a carbon-metric scaffold to track your app over time.
Guardrails: data-locality / egress backfire checks and cross-jurisdiction residency flags.
Free data only. No flow-traced consumption accounting; carbon forecast is relative, not absolute.

Roadmap: data-format/engine efficiency advice, sub-national grid zones, CI/CD integration. See docs/user-questions-backlog.md.

MCP tools

19 tools, grouped by what you're trying to do.

Pick a region

Tool	What it does
`compare_regions_tri_axis`	Rank candidate regions by carbon with cost + latency tradeoffs; recommend a pick, each axis rated R/Y/G. Pass `regions` to rank only the ones you'd actually consider.
`greener_alternative_to`	"You picked X — the greenest region within +N ms latency is Y (−Z% carbon, Δcost)." The core nudge.
`region_carbon_now`	Current gCO₂/kWh for a region, with source + timestamp + freshness — and, when live, whether that's cleaner, dirtier or about usual for that hour this month.

Time a job (scheduling)

Tool	What it does
`cleanest_hours_to_run`	Cleanest recent hours to time a deferrable job (ETL, backups, training), + % reduction. Pass `window_hours` for a job of known duration → cleanest contiguous window to start at.
`cleanest_time_of_day`	For a recurring job (nightly batch): the region's cleanest time of day, averaged across recent days. A daily pattern, not a 7-day weekly one.
`greenest_regions_on_average`	Which regions are cleanest on a typical day in a given month (or the whole year), ranked from last year's real data. Offline, no keys; a planning view, not today's grid.
`carbon_forecast`	Forward-looking: which upcoming hours will be cleanest, from the EU day-ahead wind+solar forecast (ENTSO-E). Relative ranking; US/uncovered zones degrade to the recent historical pattern.

Estimate a workload's carbon

Tool	What it does
`estimate_workload_carbon`	Rough kgCO₂/month for a workload in a region (an estimate, not a measurement).
`estimate_training_carbon`	Carbon of a GPU training run (TDP-based energy × live grid), with greener where (region ranking) + when (cleanest hours) — the two levers that compound for portable, deferrable training.
`estimate_inference_carbon`	Energy + CO₂ of an LLM inference workload, by model size class × output tokens × requests (× live grid). A low–high band; smaller size class is the big lever. Self-hosted-friendly; not a named-model leaderboard.

Efficiency & guardrails

Tool	What it does
`greener_instance_family`	A greener same-size family in the same region via perf-per-watt (newer generation / ARM Graviton-class does the same work on less energy).
`rightsizing_check`	Right-sizing (the #1 FinOps win) with a carbon twin: if you're over-provisioned, a smaller size cuts both cost and carbon → the right-sized target with monthly $ and kg CO₂ saving.
`offhours_check`	For dev/test/staging that doesn't need to run 24/7: the monthly $ and kg CO2 saved by running it only N hours a week. Compute only, directional.
`data_locality_egress_check`	Warn when running compute away from where your data lives backfires: directional egress $ + coarse transfer carbon, and whether a greener-region move is still a net win.
`migration_payoff`	Does moving the data to the compute's region pay off? Payback in months, one-off vs monthly egress and transfer carbon, net over 12 months. Egress only.
`region_move_justification`	A short paste-ready paragraph for a pull request or decision record, with the carbon, cost, latency and egress numbers and their quality labels. Says so if the move is not an improvement.
`serving_pattern_advice`	For a user-facing platform: serve from one region or several? Traffic-weighted latency + carbon, with the multi-region data-sync egress and cross-jurisdiction residency catches.

Instrument & understand

Tool	What it does
`carbon_metric_scaffold`	Emits paste-in instrumentation (Python) so your app reports its own estimated carbon over time — observable proxies × GreenPick's power model × live grid. Self-tracking, directional; not a runtime meter.
`explain_methodology_and_limits`	The assumptions and what GreenPick explicitly does not claim.

Data sources (free; swappable behind one interface)

EIA-930 (US balancing authorities) and ENTSO-E (EU zones) — live grid carbon, auto-routed by region. Both also drive cleanest_hours_to_run from recent hourly history.
Hydro-Québec (Montreal / Québec City regions) and IESO (Toronto regions) — live hourly generation by source, public, no key needed. Hydro-Québec figures arrive 1.5–6 h late, so the latest complete hour is used and its timestamp shown.
Typical — the offline default and fallback: for each region, this calendar month's average intensity and average hour-of-day profile (UTC), computed from 12 months of real hourly EIA-930 / ENTSO-E data (data/typical.json, refreshed by scripts/refresh_typical.py). Labelled quality: "typical" — a realistic norm, never presented as a current reading.
Annual — for Singapore, Tokyo, Mumbai/Pune and Sydney, where no free hourly data exists: the country's yearly lifecycle grid intensity from Ember (via Our World in Data, CC BY 4.0), with source and year (data/annual.json). Labelled quality: "annual_average"; fine for comparing regions, but carries no timing signal.
**Mock

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

GreenPick

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

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

AI Deprecations

README from the maker

Features

Contents

Why this exists

What it is / is NOT

How it differs from what's out there

Scope

MCP tools

Pick a region

Time a job (scheduling)

Estimate a workload's carbon

Efficiency & guardrails

Instrument & understand

Data sources (free; swappable behind one interface)