kundeavis-mcp

kundeavis-mcp

MCP server that queries Norwegian grocery store flyers (kundeaviser) to help AI agents plan cheap meals based on current offers.

Category
Visit Server

README

kundeavis-mcp

An MCP server that makes Norwegian grocery kundeaviser (weekly store flyers) queryable by an AI agent, so it can plan cheap meals from what's actually on offer this week.

Roughly 1,800 offers a week across 16 chains — KIWI, REMA 1000, MENY, Extra, SPAR, Coop Mega/Prix, Bunnpris, Joker, Obs, Matkroken, Nærbutikken, Jacobs, Europris, Gigaboks, Holdbart — normalised to comparable unit prices and tagged with canonical ingredients.

you: plan three cheap dinners for this week
agent: [cheapest_by_category category=meat]
       → sausage 55 kr/kg at Obs, pork chop 69.90 kr/kg at Obs, pork neck 89.90 kr/kg at Coop Prix

Install

Requires Node 22.5+ (it uses the built-in node:sqlite, so there is no native module to compile).

Not on npm yet — install from the repo. dist/ is built during install:

npm i -g github:donadelicc/kundeavis-mcp
{
  "mcpServers": {
    "kundeavis": { "command": "kundeavis-mcp" }
  }
}

The first query fetches the current flyers automatically (about 45 HTTP requests, a few seconds) into ~/.kundeavis-mcp/offers.db. Nothing else to set up.

Each machine keeps its own database and its own archive. Two agents on two machines start with two separate histories — see below if you want them to share one.

Tools

Tool What it answers
cheapest_by_category "What protein is cheap this week?" Cheapest offer per ingredient, ranked by unit price. The main meal-planning entry point.
search_offers Free-text plus filters on ingredient, category, chain, unit-price basis, discount.
compare_ingredient One ingredient priced across every chain, against a baseline from earlier weeks.
price_history Cheapest unit price per week per chain, to judge whether a "tilbud" is genuinely good.
find_stores Grocery stores near a coordinate. Offers are chain-national, so this answers which shop to go to.
list_chains Coverage per chain: offers, how many have a usable unit price, how many are tagged.
sync Force a refresh. Runs automatically when nothing valid is cached.

There is no history upstream — capture it or lose it

This is the single most important thing to know before relying on this tool.

Offers vanish at their own run_till, with no grace period. Watched live across a week rollover: at two minutes past expiry, a KIWI "Uke 30" catalog served 12 of the 79 offers it had served minutes earlier — and all 12 survivors were two-week offers running to 2 August. Everything scoped to the week itself was already unreachable. /offers serves only what is valid at request time.

And old catalogs are deleted outright. Verified against real expired IDs recovered from archived mattilbud.no HTML: a KIWI catalog from May 2024 and three Danish ones from 2020 all return CATALOG_NOT_FOUND, byte-identical to the response for an ID that never existed. (A just-expired catalog's record lingers a while — it still answered 200, still claiming offer_count: 85 — but the offers behind it were already gone, which is the only part that matters.)

There is no archive endpoint and no backfill. offset past the end returns [], and date or ordering parameters are accepted but silently ignored.

Two traps worth knowing:

  • offers?catalog_id=<expired> returns HTTP 200 with an empty array, not an error. A backfill attempt looks like it worked and stores nothing.
  • offer_count overstates what /offers will ever return — MENY's "Uke 31" claims 151 and serves 70, before and after the flyer activates. It is not a timing artefact and not a pagination bug; the reachable set is simply smaller. Reported as a shortfall.

What the listing gives you is lookahead, not lookback: next week's flyer appears before it activates, but a week drops off the moment it ends. Once run_till passes there is nothing to go back for. Miss a week and it is gone permanently. So:

kundeavis-mcp schedule --install   # twice daily, macOS launchd

launchd rather than cron specifically because a job missed while the Mac was asleep runs on the next wake; cron just skips it, and a skipped Saturday is an unrecoverable week. Runs pass --if-stale, which decides locally — most fire and exit having made zero HTTP requests.

What to back up

Three tiers, and only the middle one matters:

~/.kundeavis-mcp/offers.db derived cache don't back up — rebuildable
~/.kundeavis-mcp/history/*.ndjson.gz raw API payloads, immutable this is the asset
a private git repo off-machine copy recommended

The archive stores the raw payloads, not normalized rows, because the unit-price parser is still improving — archiving today's output would freeze today's bugs into a history that can never be re-derived. kundeavis-mcp import replays snapshots through the current normalizer, so every future parser fix retroactively improves every week you have ever captured.

Snapshots are ~380 KB gzipped per sync, so a year is roughly 20–40 MB. They are named to the second and never overwritten: the API does not serve a stable set (two syncs 35 minutes apart returned 1,786 and 1,782 offers, four present only in the first), so collapsing them would quietly drop offers. Replay unions snapshots, and conflicts resolve to the best-evidenced copy rather than the last one written.

Back it up somewhere private. Please don't commit offer data to a public repo — it isn't ours to redistribute, which is the whole basis on which this project queries the API client-side.

kundeavis-mcp history    # what you have captured
kundeavis-mcp import     # rebuild the database from it, no network

Unit prices: read the confidence field

Comparing groceries means comparing unit prices, and flyer data makes that easy to get wrong. KIWI's "HAMBURGER 79,90 / 4 x 100 g" is 199.75 kr/kg, not 799 — the pack total is pieces × size × SI factor, and ignoring pieces is wrong by 4×.

Descriptions often repeat the retailer's own printed unit price, so every computed value is cross-checked against it. Each offer carries the outcome:

unit_price_confidence Meaning
verified Our value matches the kr/kg or kr/l figure printed in the flyer.
computed Derived from the pack data, but nothing comparable was printed — or the source is internally ambiguous (see notes).
unavailable We declined to serve a number. unit_price is null.

On a live week: 98.3% of checkable offers verified (865 / 880), and 15 of 1,782 offers (0.8%) had their unit price withheld. Those are genuine source inconsistencies — Coop's member-vs-non-member pricing, a flyer quoting drained weight while the API reports gross, Tjek reporting pieces: 1 for a multipack. A withheld value is deliberate: a confidently wrong kr/kg is the worst thing a price-comparison tool can do.

Two more rules the tools follow:

  • Never mix bases. unit_price_basis is kg, l or pcs. A per-piece price is not comparable to kr/kg — "pr. pk" and "/STK" both mean pieces but one is a pack and the other an item — so pcs offers are excluded from cheapest-first rankings.
  • Two different discount numbers, never conflated. discount_pct is the retailer's own claim, from the flyer's pre-price, and is null for ~83% of offers. vs_baseline_pct is our inference from stored history. The second is never presented as the first.

"This week" means valid right now, not the current ISO week. Flyers change over on Saturday or Sunday, so those differ by a day or two every week.

Ingredient coverage

The upstream API returns no categories at all (category_ids is empty on every Norwegian grocery offer), and headings are retail shorthand — GULOST&CHEDDAR, NAKKEKOTELETT, REKER I LØSVEKT. So data/ingredients.yaml maps them to canonical ingredients, and it is the most useful thing to contribute to.

Currently ~57% of offers carry an ingredient tag. The untagged remainder is mostly brand-specific compound names and non-food. To help:

kundeavis-mcp headings          # ranked worklist of what isn't covered
# add aliases to data/ingredients.yaml
kundeavis-mcp retag             # re-tag locally, no network, prints the new coverage
node test/taxonomy-lint.mjs     # catches aliases that can never fire

Matching is whole-token, not prefix or substring. An alias matches when it equals the heading or appears in it delimited by spaces, so SVINEKOTELETT matches SVINEKOTELETT MED BEN but not SVINEKOTELETTER — Norwegian inflection is not handled for you, and you should enumerate the forms you expect. Æ, Ø and Å survive normalization; other diacritics are folded, so write ENTRECOTE. Add the ingredient word, not the brand.

Run the lint before opening a PR. A duplicate alias fails silently — the first ingredient to claim it wins and the second never fires — which is how RIBBE ended up meaning spareribs rather than juleribbe, and PINNEKJØTT sat on lamb despite selling at a multiple of fresh lamb's price per kg.

The taxonomy also carries seasonal vocabulary written ahead of the season (jul, påske, fårikål, grillsesong). Since expired flyers can't be re-fetched, waiting to observe RIBBE or PINNEKJØTT would mean poor coverage every December. Those entries are inert in July and cost nothing to carry; correct them against real headings when the season arrives.

An optional LLM fallback resolves unknown headings and appends them to data/learned.yaml, with low-confidence answers diverted to needs_review.yaml. It is off by default — a routine sync should not spend money unless you asked:

KUNDEAVIS_LLM=1 ANTHROPIC_API_KEY=... kundeavis-mcp sync

Data source

Offer data comes from the read endpoints of Tjek (formerly ShopGun / eTilbudsavis), the platform Norwegian retailers publish their flyers through and which sites like mattilbud.no are built on. Retailers submit hotspot metadata, so offers arrive already structured — there is no OCR here.

Please read this before depending on it. That API is undocumented, not published open data. It happens to serve these reads unauthenticated, but it advertises X-Api-Key/X-Token in its CORS headers, which suggests a permissive default rather than a public contract. It can change or close at any time.

Accordingly:

  • This project is not affiliated with, endorsed by, or connected to Tjek, mattilbud.no, or any retailer. All trademarks belong to their owners.
  • No offer data is redistributed. Every install queries upstream itself and caches locally. What ships in this repo is our own code and taxonomy.
  • The client is deliberately gentle: concurrency capped at 4, exponential backoff, an identifying User-Agent, and aggressive caching. A full national sync is ~45 requests. Please don't raise those limits.

MIT licensed — covering this project's code and the ingredient taxonomy, not upstream data.

Development

bun install
bun run build                      # tsc -> dist/
bun run test                       # taxonomy lint + archive round trip + unit prices
bun run validate:unitprice         # correctness gate: computed vs printed, live week
node test/taxonomy-lint.mjs        # alias collisions, categories, shape (no network)
KUNDEAVIS_HISTORY=./dev-history node test/archive-roundtrip.mjs   # replay + union
node test/mcp-smoke.mjs            # end-to-end MCP over stdio
KUNDEAVIS_DB=./dev.db KUNDEAVIS_HISTORY=./dev-history node dist/cli.js sync
KUNDEAVIS_DB=./dev.db node dist/cli.js stats

test:archive needs a snapshot to work from, so run a sync first.

bun is fine for dev, but the server itself runs on Node — Bun does not implement node:sqlite.

Env var Default
KUNDEAVIS_DB ~/.kundeavis-mcp/offers.db
KUNDEAVIS_HISTORY ~/.kundeavis-mcp/history
KUNDEAVIS_DATA the packaged data/ directory
KUNDEAVIS_LLM unset (LLM fallback off)
ANTHROPIC_API_KEY — required only with KUNDEAVIS_LLM=1

Known limitations

  • Offers are chain-national. The API exposes no per-store pricing (store_id is empty on every offer), so a regional price difference is invisible. find_stores is a separate lookup.
  • Regional catalog duplicates are collapsed, not merged. Chains publish one catalog per region — Holdbart ships 26 with identical labels — and we keep the richest variant per (chain, label, date range). Fetching all of them would triple our request count for near-identical data.
  • Catalog metadata overstates its own contents. A catalog claiming 80 offers may only expose 73 at any offset. Reported as a shortfall, not treated as an error.
  • Price history starts when you do, and cannot be backfilled. See above. Baselines only cover weeks this installation captured while they were live.
  • The baseline is built from other weeks' offers, which are also discounts. vs_baseline_pct therefore compares a sale price against other sale prices and will understate how good a deal is. Accumulating more weeks does not remove that bias; only a shelf-price reference would. Read it as "cheap for a tilbud", not "cheap".
  • Long-running seasonal magazines carry no structured offers (Coop Mega's "Sommermat", Joker's "Den gode sommermaten"). The weekly flyers that matter for price hunting all do.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured