# The Google Health API Got a CLI: ghealth is an Open-Source Tool for Your Fitbit Air Data

> Source: <https://www.marktechpost.com/2026/07/02/the-google-health-api-got-a-cli-ghealth-is-an-open-source-tool-for-your-fitbit-air-data/>
> Published: 2026-07-02 08:46:56+00:00

The ** Google Health API **is the official successor to the Fitbit Web API. It targets the Google Health API v4 and moves developers onto Google OAuth 2.0. Now an open-source CLI command-line tool called

`ghealth`

wraps that API for terminals and AI agents.The tool is a single Go binary under the Apache 2.0 license. It exposes 40 verified data types as structured JSON. That design lets you pipe sleep, heart rate, and step data into an agent’s context.

**What is ghealth?**

`ghealth`

is a wrapper over the Google Health API v4. You build it from source with `go build -o ghealth .`

. It ships as one self-contained binary.

The tool is explicitly agent-first. Every command returns simplified JSON with a stable shape. It also provides deterministic exit codes, a `--dry-run`

flag, and a `--raw`

flag.

The repository ships two Agent Skills as `SKILL.md`

files. One covers auth, setup, and global flags. The other documents all 40 data types, operations, patterns, and gotchas. Agents install them with `npx skills add`

.

The CLI lives under the `Google-Health-API`

GitHub organization. That organization also hosts long-standing Fitbit open-source repositories.

**The Data Surface: 40 Verified Types**

The 40 types cover most Fitbit and Pixel Watch signals. Examples include `steps`

, `heart-rate`

, `sleep`

, `weight`

, `oxygen-saturation`

, and `heart-rate-variability`

. Clinical types like `electrocardiogram`

require the `ecg.readonly`

scope.

Each type supports a subset of operations. Common ones are `list`

, `rollup`

, `daily-rollup`

, and `reconcile`

. Writable types (`exercise`

, `sleep`

, `weight`

, `body-fat`

, `height`

) add `create`

, `update`

, and `delete`

.

The `reconcile`

operation merges overlapping data points from multiple sources. That mirrors the Reconciled Stream in the v4 API.

Sleep is a good example for pattern analysis. The default `list`

returns a summary. Adding `--detail`

returns stage-by-stage data (awake, deep, REM). That helps you spot patterns week over week.

**Setup: What Actually Happens**

Setup runs through one command: `ghealth setup`

. A wizard walks you through the GCP project and OAuth. You create a Desktop-type OAuth client in the Google Cloud Console.

You bring your own OAuth credentials. The tool holds no shared key. Files are written under `~/.config/ghealth/`

with file mode 0600. Tokens refresh automatically.

All Google Health API scopes are classified as Restricted. Google requires a privacy and security review for production access. For personal use, you authorize your own project against your own account. The API returns data from Fitbit, Pixel Watch, and connected third-party sources.

The headless flow uses PKCE with an S256 challenge. It also validates a random `state`

parameter on completion.

**Hands-On: Commands and Output**

Reading data is consistent across types. Every read returns an object with rows under `dataPoints`

.

```
# Recent heart rate readings
ghealth data heart-rate list --from today --limit 10

# Daily step totals for a week
ghealth data steps daily-rollup --from 2026-03-22 --to 2026-03-29

# Sleep stages for the last five nights
ghealth data sleep list --limit 5 --detail
```

Step totals return aggregated JSON:

```
{
  "dataPoints": [
    {"date": "2026-03-28", "countSum": "9037"},
    {"date": "2026-03-27", "countSum": "2408"}
  ]
}
```

Output is simplified by default. Use `--raw`

for the original API response. Use `--format csv`

or `--format table`

for other shapes. The `-o`

flag writes a file and prints a schema preview.

Pagination is lossless. A large `list`

returns a `nextPageToken`

. You pass it back with `--page-token`

to fetch the next page.

**Use Cases With Examples**

**Feed sleep patterns into an agent**: Pull several nights with`--detail`

. Pipe the JSON into a Claude Code or Codex session. Ask the agent to summarize deep-sleep trends over the week.**Load workouts into pandas**: Run`ghealth data exercise export-tcx --id <id> --output ride.csv --as csv`

. Each row is one trackpoint with heart rate and GPS. Then run`pd.read_csv`

on the file.**Build a resting heart-rate view**: Query`daily-resting-heart-rate`

over 30 days. Emit CSV with`--format csv`

. Chart it in a notebook or a dashboard.

**How ghealth Compares**

The table below sets `ghealth`

against the raw API and two other CLIs. The other two CLIs both self-identify as unofficial.

| Attribute | ghealth (this CLI) | Google Health API v4 (direct REST) | rudrankriyam/Google-Health-CLI | googlehealth-cli (npm) |
|---|---|---|---|---|
| Install | `git clone` + `go build` | None; call HTTP/gRPC yourself | Build from Go source | `npm i -g googlehealth-cli` |
| Language | Go, single binary | Any | Go | Node.js |
| Auth | Your own OAuth client, PKCE S256 | Google OAuth 2.0 | Your own OAuth client | Your own OAuth client |
| Agent output | Simplified JSON, exit codes, `SKILL.md` | Raw JSON / gRPC | Predictable JSON | Stable `--json` envelope |
| Data types | 40 verified against live API | Full v4 surface | Tracks documented v4 surface | Subset of types |
| Official status | No; community, in Google-Health-API org | Yes; Google | No; states unofficial | No; states unaffiliated |

For raw control, the direct REST API is the ground truth. For terminal and agent use, `ghealth`

reduces auth and formatting boilerplate.

**Interactive Explainer**

Check out the ** Repo**.

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Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.

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