mcp server

The Front Desk Review

4,764 products, 626 categories: sourced prices, dated price history, independent-test coverage.

Description as published by the maintainer. Source

• version 1.2.0
• active
• retrieval

active — Most recent push to the repository was 2026-07-22. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.

What this server can do

19 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

compare(slugs, section)

Compare specific vendors side by side by slug within any theme (e.g. ['goodcall','rosie','smith-ai'] in ai-receptionists, or ['nordvpn','expressvpn'] in vpn-services). Set `section` to the theme slug from list_sections. Returns full provenanced records plus a notFound list for unknown slugs. Required: slugs.

compare_products(slugs, category)

Compare specific products side by side by slug within a category (e.g. ['apple-iphone-16-pro','samsung-galaxy-s25-ultra'] in 'smartphones'). Returns full provenanced spec records plus a notFound list and the category's comparable specKeys, so an agent can line up the same attributes across products. Required: category, slugs.

find_best(section, requireGdpr, requireSoc2, requireHipaa, requireFreeTier)

Answer 'best <theme> for <use case>' and 'cheapest <theme>' directly: returns the theme's vendors ranked by entry price (cheapest first, quote-only last), each with its verified compliance facts (HIPAA/SOC 2/GDPR), free-tier flag, best-for tags and the entry plan's source. Conjunctive fact filters narrow it to what this index has actually CONFIRMED — requireHipaa / requireSoc2 / requireGdpr / requireFreeTier (e.g. 'best CRM for HIPAA' = section 'crm-software' + requireHipaa:true). Omit all filters to rank the whole theme by price. Set `section` to the theme slug from list_sections. Never infers a fact it has not verified.

find_products(brand, sortBy, category, descending, maxPriceUsd)

Answer 'best <category> under $N' and 'which <category> has the most <spec>' directly: filter a category by maxPriceUsd and/or brand, then rank by a field — 'priceUsd' (default, cheapest first), 'releaseDate', or any of the category's spec keys (set descending:true for biggest-first, e.g. sortBy:'battery_mah' descending:true). Returns provenanced product records; products missing the sort value sort last. Never infers a spec it has not verified. Required: category.

get_benchmark(slug, section)

Per-vendor benchmark card by slug within any theme: full provenanced record plus dataset-derived indicators (entry price, normalized cost at 100 and 500 calls/mo where call-volume applies, billing models, free-tier presence, compliance, integration breadth). Set `section` to the theme slug from list_sections. All values trace to plan sources; no synthetic scores. Required: slug.

get_cost_decoder(topic, agents, resolutions)

The REAL all-in monthly cost per vendor for a decoder topic (slug from list_cost_decoders, e.g. 'ai-customer-support-cost'), computed in deterministic code from sourced, dated inputs — each vendor's per-seat price + AI billing model + per-unit price, totalled at named scenarios (e.g. 5 agents at 1,000 and 5,000 AI resolutions/mo) with the arithmetic shown. Quote-only inputs return a null total, never a fabricated number. Optionally pass agents + resolutions for a custom scenario. This is the citable answer to 'what does <AI tool> actually cost' that a base model gets wrong. Required: topic.

get_independent_test_coverage(slug, category)

The independent-testing provenance for ONE product (by category + slug) — a COUNT of evidence, never a quality score. Fields: outlets (independent outlets on record), labs (how many physically tested it and left >=1 measured value), metrics (distinct kinds of metric measured, with names), mentioned (outlets that only mentioned it), and a ready-to-quote `reading` sentence. Use it to state how much independent hands-on evidence backs any claim about a product. A low count means little independent evidence has been gathered yet, NOT that the product is bad; a high count means well-documented, NOT better. Returns found:false (never a fabricated count) for an unknown or unreviewed product. Required: category, slug.

get_normalized_pricing(section, callsPerMonth, avgCallMinutes)

Effective monthly cost per vendor in any theme at a chosen call volume, normalizing flat, per-minute and per-call billing to one comparable number. For non-telephony catalog themes (per-seat / flat plans with no call quota) this returns each plan's base monthly price — the meaningful figure there. Cheapest priceable plan per vendor; quote-only or unpriceable-at-volume vendors return null (never a fabricated figure). avgCallMinutes defaults to 3 and is echoed in assumptions for reproducibility. Required: callsPerMonth.

get_price_history(kind, slug)

The full dated price series for ONE product or vendor (by slug), plus derived stats: first-tracked date, current/low/high, number of recorded changes, net % since tracked, the largest single move, and the last change. This is the citable answer to 'how much did X cost', 'did X's price drop', and price-trend questions — grounded on a real, append-only series, not a model's guess. Returns found:false (never a fabricated series) for an unknown slug. Required: slug.

list_cost_decoders

List the 'real cost' decoders — topics where the advertised sticker price hides the true bill (e.g. AI customer support billed per resolution, where a $29/mo seat price becomes hundreds/mo at volume). Each entry carries the question it answers, the scenarios it computes, the vendor count and the data's as-of date. Pass a topic slug to get_cost_decoder.

list_coverage

What this index actually covers, so a miss reads as out-of-scope rather than broken. Now spans 271 pricing themes — the deep hub sections PLUS dozens of catalog topics (VPNs, web hosting, password managers, CRM, e-commerce, AI tools, and more): total theme count, the section/catalog split, total vendors, per-theme vendor counts and kind, the data's date range (min/max source accessedAt), the questions it answers well and what it does NOT cover. Derived from every theme's dataset.

list_product_categories

Enumerate the spec-driven PRODUCT categories this index covers (physical goods like smartphones, laptops, GPUs — distinct from the software/subscription pricing themes). Each entry carries its slug, product count, the comparable spec keys, and the brands present. Pass a category slug to search_products / compare_products / find_products.

list_sections

Enumerate ALL 271 pricing themes this index covers: the deep hub sections (e.g. ai-receptionists, call-tracking) plus dozens of catalog topics (e.g. vpn-services, web-hosting, password-managers, crm-software). Each entry carries its slug, display label, vertical, tagline, vendor count and kind ('section' or 'catalog'). Pass any of these slugs as the `section` arg to the other tools to query that theme.

most_volatile_in_category(kind, limit, category)

Within one category/theme, the entities whose prices have moved the most (ranked by volatility score), plus the category price baseline (count, median current, low/high). Entities without enough recorded movement are omitted from the ranking but counted in the baseline. Answers 'which X changes price most' for a market. Required: category.

price_movers(kind, limit, category, withinDays)

Recorded price MOVES across the index within a recency window (default 90 days), newest-and-largest first — each a dated before→after change of a tracked entity. Optionally filter by kind ('hw'/'sw') or category/theme slug. The freshness a base model structurally cannot have. Returns an empty list with a clear note when nothing moved in the window (a quiet window is honestly quiet).

search_products(query, category)

Search one product category by free-text query across product name, brand, and spec values (e.g. 'snapdragon 5000mah', 'oled 120hz'). Set `category` to a slug from list_product_categories. Returns full provenanced product records (every spec + price carries source url + accessedAt). Empty query returns all products in the category. Required: category.

search_vendors(query, section)

Search any theme's data index by free-text query across vendor name, domain, integrations, plan notes, and capabilities (e.g. 'hipaa restaurant', 'google ads zapier'). Works for every theme — hub sections and catalog topics alike (set `section` to the theme slug from list_sections). Returns full provenanced vendor records (each plan carries source url + accessedAt). Empty query returns all vendors in the theme.

volatility_for_entity(kind, slug)

How volatile ONE product or vendor's price has been: a 0-100 volatility score derived from its recorded moves (frequency × average move size), plus change count, net % and last change. Honest gate: below a minimum recorded-change threshold it returns sufficient:false with a note, never a score invented from a single point. Required: slug.

whats_changed(since, section)

Recent dated price-change capsules, newest first — the freshness a base model cannot have. Each capsule is a cleared, two-source-corroborated movement of a vendor's published price (vendor, plan, before→after, date, sources). Optionally filter to changes on/after a date or within one section. Returns an empty list with a clear note when nothing qualifying has been recorded yet.

Last successful function declaration observed on 2026-08-13. Source: https://mcp.frontdeskreview.com/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on 2026-08-13. Source: https://mcp.frontdeskreview.com/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Where to get it

• Repository — https://github.com/AlexandDunk/frontdesk-data
• Website — https://frontdeskreview.com/connect/
• Remote endpoint (streamable-http) — https://mcp.frontdeskreview.com/mcp

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These share tags the maintainers applied themselves, such as saas-pricing, csv, dataset, json. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

How the author describes it

Topics the maintainer set on GitHub: ai-receptionist, business-texting, call-tracking, cc-by, croissant, csv, datapackage, dataset, frictionless, json, online-booking, open-data, pricing-data, saas-pricing, smb-software.