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walmart

Quick start

Run your first walmart commands and shape their output.

Once walmart is on your PATH, complete a search box. suggest reads the typeahead host and answers from any network:

walmart suggest keyboard -n 6 --fields term

╭─────────────────────────────╮
│ TERM                        │
├─────────────────────────────┤
│ keyboard                    │
│ keyboard and mouse          │
│ keyboard and mouse wireless │
│ keyboard piano              │
│ keyboards for computers     │
│ keyboard wireless           │
╰─────────────────────────────╯

The department tree reads from the homepage, which Walmart serves anonymously:

walmart category tree --fields id,name

By default you get an aligned table on a terminal. Ask for JSON when you want to pipe it:

walmart suggest keyboard -o json

[
  {
    "query": "keyboard",
    "term": "keyboard and mouse",
    "image": "https://i5.walmartimages.com/asr/..."
  }
]

The best-effort surfaces

The product, search, category, and store pages sit behind Walmart's bot wall and may exit 4 from a datacenter. See what anonymous access reaches.

walmart product 5037034321           # one product by id (best-effort)
walmart search "air fryer"           # keyword search (best-effort)
walmart category browse 3944         # the items in a category (best-effort)
walmart deals                        # the current rollbacks (best-effort)
walmart store find 94040             # stores near a ZIP (needs credentials)

Set WALMART_CONSUMER_ID and an Affiliate API private key and these commands fall back to the documented API on a wall. See configuration.

Shape the output

The same flags work on every command:

walmart category tree --fields id,name
walmart product 5037034321 --template '{{.Name}} {{.Price}} {{.Currency}}'
walmart suggest keyboard -o jsonl | jq .term

-o takes table, json, jsonl, csv, tsv, url, or raw. Left to auto, it prints a table to a terminal and JSONL into a pipe, so the same command reads well by hand and parses cleanly downstream. See output formats for the full contract.

Resolve a reference offline

The ref commands classify and build Walmart references with no network call:

walmart ref id "https://www.walmart.com/ip/Apple-iPhone-13/123456789012"
walmart ref url product 5037034321

Serve it instead

The same operations are available over HTTP and to agents over MCP:

walmart serve --addr :7777 &
curl -s 'localhost:7777/v1/suggest/keyboard'   # NDJSON, one record per line
walmart mcp                                     # MCP over stdio

The guides cover the common jobs, and the CLI reference is the full command tree and flag list.

2 min read