# ratebook [Health: Active]

**Category:** 💻 Developer Tools  
**Repository:** https://github.com/cbetz/ratebook  
**GitHub Stars:** 1  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/ratebook

## Description
Open MCP server for US electricity tariffs: real rate lookup, bill estimates, and when to charge.

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: high). Install path detected from listing signals. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "ratebook": {
    "url": "https://img.shields.io/badge/code-Apache--2.0-blue.svg)](LICENSE"
  }
}
```

## Documentation & README

# Ratebook

The open rate engine for the electrified home — an openly licensed database of US electricity
tariffs, an open-source rate-calculation engine, and an MCP server, so any app, device, or agent
can answer "what will this kWh cost me, and when should I charge?"

[![License: Apache-2.0](https://img.shields.io/badge/code-Apache--2.0-blue.svg)](LICENSE)
[![Data: CC0-1.0](https://img.shields.io/badge/data-CC0--1.0-lightgrey.svg)](LICENSE-DATA)
[![Python 3.12+](https://img.shields.io/badge/python-3.12%2B-blue.svg)](https://www.python.org/)
[![CI](https://github.com/cbetz/ratebook/actions/workflows/ci.yml/badge.svg)](https://github.com/cbetz/ratebook/actions/workflows/ci.yml)

![Ratebook demo — estimate a monthly bill, and see how charging an EV off-peak is ~23% cheaper, computed live by the engine](https://raw.githubusercontent.com/cbetz/ratebook/HEAD/demo/ratebook-demo.gif)

<sub>↑ The real engine running in the browser. Try it yourself: [`demo/demo.html`](https://github.com/cbetz/ratebook/blob/HEAD/demo/demo.html).</sub>

> **Status: pre-release.** What works today: a deterministic rate engine (Python + a TypeScript
> port held to it byte-for-byte), cross-validated against NREL's PySAM and shown to reproduce a
> real bill's total once its components are supplied; an LLM pipeline that extracts tariff
> structure from utility PDFs; an MCP server; and a Home Assistant integration. What's still in progress: broad utility coverage, freshness automation,
> and a reproducible public accuracy scorecard. See [`docs/ROADMAP.md`](https://github.com/cbetz/ratebook/blob/HEAD/docs/ROADMAP.md).

## Quickstart

The engine has no I/O and no required data download — price a tariff in a few lines:

```sh
git clone https://github.com/cbetz/ratebook && cd ratebook
uv sync
uv run python quickstart.py   # or paste the snippet below into `uv run python`
```

```python
from datetime import date
from decimal import Decimal
from ratebook import (
    Tariff, TariffIdentity, Sector, EnergyRateStructure, EnergyPeriod, EnergyTier,
    Schedule, FixedCharge, FixedChargeUnit, Usage, BillingWindow, estimate_bill,
)

# A flat residential tariff: $0.10276/kWh + $11.30/month (PECO Rate R distribution).
no_tou = tuple(tuple(0 for _ in range(24)) for _ in range(12))  # 12 months × 24 hours, one period
tariff = Tariff(
    energy=EnergyRateStructure(periods=(EnergyPeriod(tiers=(EnergyTier(rate=Decimal("0.10276")),)),)),
    schedule=Schedule(weekday=no_tou, weekend=no_tou),
    identity=TariffIdentity(plan_code="R", plan_name="Example flat residential", sector=Sector.RESIDENTIAL),
    fixed_charges=(FixedCharge(Decimal("11.30"), FixedChargeUnit.PER_MONTH),),
)

bill = estimate_bill(tariff, Usage.aggregate(1244), BillingWindow(date(2026, 4, 28), 30))
print(f"ok={bill.ok}  total=${bill.total}")   # ok=True  total=$139.13344  →  1244 kWh × $0.10276 + $11.30
```

Real tariffs round-trip through JSON via `Tariff.from_json(...)`. To work with corpus data, load
the URDB seed set (`uv run ratebook-data urdb`) or run the MCP server (`uv run ratebook-mcp`) and
ask an agent `lookup_tariff` / `estimate_bill` / `compare_plans` / `best_charge_window`.

## Development

Python 3.12+, [uv](https://docs.astral.sh/uv/) workspace with these packages:
`packages/ratebook` (rate engine), `packages/ratebook-data` (data plant),
`packages/ratebook-mcp` (MCP server), `packages/ratebook-ts` (the TypeScript engine port —
pnpm + vitest, held to the Python engine via shared JSON test vectors), and
`packages/ratebook-homeassistant` (a Home Assistant custom integration: electricity-price +
cheapest-charge-window sensors).

```sh
uv sync                            # install all workspace packages + dev tools
uv run pytest                      # Python tests
uv run ruff check .                # lint
uv run ratebook-data urdb          # download URDB bulk CSV → data/raw/, load into data/ratebook.duckdb
uv run ratebook-mcp                # run the MCP server (stdio)

pnpm -C packages/ratebook-ts install && pnpm -C packages/ratebook-ts test   # TS engine + vectors
```

The PySAM cross-validation runs in CI against committed tariff fixtures (`uv sync --group
validation` installs the oracle). The MCP tool tests additionally need the built corpus and run
locally (`uv run ratebook-data urdb`); they skip otherwise. The two engines must never
diverge: both reproduce `packages/ratebook/tests/vectors/v0_bills.json` byte-for-byte. Regenerate
it with `uv run python packages/ratebook/tests/generate_vectors.py`.

See [`CONTRIBUTING.md`](https://github.com/cbetz/ratebook/blob/HEAD/CONTRIBUTING.md) — the highest-value contribution is a **tariff
correction** (report a wrong or stale rate with its source PDF).

## License

Code is licensed under [Apache-2.0](https://github.com/cbetz/ratebook/blob/HEAD/LICENSE). Published datasets are dedicated to the public
domain under [CC0-1.0](https://github.com/cbetz/ratebook/blob/HEAD/LICENSE-DATA). The seed corpus derives from the
[U.S. Utility Rate Database](https://apps.openei.org/USURDB/) (CC0).