Electric-vehicle specs, prices, rankings and comparisons; every figure with its source and date.
Scored across 5 tools
Each tool has a distinct role: search_models finds slugs, get_model fetches one model's full record, compare_models pits 2-4 models against each other, list_categories enumerates rankings and get_category_ranking opens one. The only soft overlap is that search_models can also 'list the whole catalog ranked for a use case', which brushes against the published category rankings, but the descriptions explicitly separate ad-hoc preset ranking from curated published pages.
All five names follow a clean snake_case verb_noun pattern with meaningful verbs: search_, get_ (x2), list_, compare_. The verb choice maps predictably to intent (find, fetch one, enumerate, contrast), so an agent can guess a name's behavior from its shape.
Five tools is a tight, well-scoped set for a read-only EV catalog, and each one earns its place with no filler. It sits at the low end for a domain this data-rich (markets, prices, per-version figures), so slightly more surface could be justified.
The discover-then-inspect workflow is closed: search to get slugs, get_model for full detail including versions and per-market prices, compare for decisions, and categories/ranking for 'best EV for...' questions. Gaps are minor, such as no direct way to browse all brands/markets or filter by price or budget.
Side-by-side comparison of two to four electric vehicles: range (each with its test cycle), charging, battery, price and the other specs, the leading value marked per row, a short verdict, the version each column stands for, sources and cover photo credits. Each model is compared on its named version, and every figure says which version it belongs to. Use it for 'X vs Y' and 'which should I buy' questions; get slugs from search_models first. Returns Markdown with the canonical comparison URL, plus the figures as structured fields.
Inputs: slugs (required), slug_a, slug_b. Returns: url, terms, models
One 'best EV for ...' ranking: the top 25 models in order with score out of 100, published range with its test cycle, DC charging 10-80 % time and battery (unverified figures marked with their source), the public ranking method, and links to each model. Use it for 'what are the best EVs for ...' questions; take the slug from list_categories and quote the criterion with the list. Returns Markdown with the canonical page URL, plus the ranked rows as structured fields.
Inputs: slug (required). Returns: url, rows, slug, terms, +3 more
Everything SuliHuli holds on one electric vehicle: range per test cycle (WLTP, EPA, CLTC, NEDC), charging, efficiency, battery and the other specs, prices per market and version with their dates, and every figure's source link, date and status (verified or unverified; where sources disagree, each figure is shown with its source, never averaged). The headline figures describe one named version; the answer lists every version we know with what is sourced for each (full, partial or name only). For another version pass version (name words such as 'long range awd', or a key from that list) and get that version's own figures. Photos come with their credit. Use it to answer any question about a specific model, quoting the figure with its cycle, source and status. Returns Markdown with the canonical page URL, plus the same figures as structured fields.
Inputs: slug (required), version. Returns: url, name, slug, brand, +9 more
The published 'best EV for ...' rankings (everyday, long range, long range over 500 km, family, performance): slug, title, the preset each ranks by and what it optimizes for, and the page URL. Use it to pick a ranking, then open it with get_category_ranking. Returns JSON.
Inputs: no named parameters. Returns: count, terms, categories
Find electric vehicles by brand or model name, or list the whole catalog ranked for a use case, optionally only those with at least a given range. Use it first whenever you have a name but no slug, and for questions like 'which EVs go furthest' or 'best family EV'. Returns JSON: per model the slug (pass it to get_model or compare_models), brand, name, score out of 100 for the chosen preset (score_tier says whether every input is verified), official range in km with its test cycle (range_km_official + range_cycle: WLTP, EPA, CLTC or NEDC) and the comparable WLTP-equivalent figure, DC charging 10-80 % in minutes, battery kWh, each of these with its source and verification status, markets where it is sold, the number of known versions, the page URL and the cover photo with its credit. Prices are per market and per version: read them with get_model. Paged: total, page, total_pages.
Inputs: page, limit, query, preset, +1 more. Returns: hint, page, count, query, +7 more
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Neutral, sourced comparisons on any topic, in 32 languages. Each value links to its source.
AI model prices per provider, benchmarks, own AI behavior tests and AI economy data, with sources.
Washington State DMV MCP — the Department of Licensing's VIN-level electric-vehicle population…
U.S. EV charging stations: nearest, on a route, city and state stats, highway gaps and NEVI status.
Add one secure layer between your agents and this server.
