DataDive vs BoostedTravel
A side-by-side look at the DataDive and BoostedTravel MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose DataDive for e-commerce work as a local process; choose BoostedTravel for travel & transportation as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose DataDive when
- You need dedicated capabilities in the E-Commerce domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
DATADIVE_API_KEY. - You want tools like
list_niches, get_niche_keywords, list_keyword_exclusions.
Choose BoostedTravel when
- You need dedicated capabilities in the Travel & Transportation domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
LETSFG_BEARER_TOKEN, LETSFG_API_KEY. - You want tools like
search_flights, resolve_location, unlock_flight_offer.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | E-Commerce | Travel & Transportation |
| Quality signal | 63/100 · Good | 72/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | Free |
| Required env vars | DATADIVE_API_KEY | LETSFG_BEARER_TOKENLETSFG_API_KEY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 2,189 |
| Directory activity | 1 views 0 installs 0 upvotes | 9 views 1 installs 0 upvotes |
| Tools | 43 | 14 |
| Full listing | View DataDive | View BoostedTravel |
Tools & capabilities
DataDive tools 43
list_nichesUse this first when the user asks about their niches, or to find a `nicheId` for use with `get_niche_keywords`, `get_niche_competitors`, or `get_ranking_juice`. Retrieves a paginated list of Niches, newest dive first. Each Niche represents a market segment or product category being tracked. Returns nicheId, heroKeyword, nicheLabel, marketplace (com/uk/de/...), and latestResearchDate per niche, plus pagination metadata (currentPage, pageSize, total, lastPage, hasNext, hasPrev). Narrow with `searchText` (label/keyword) or `searchAsin` (a competitor ASIN) instead of scanning pages; a page holds at most 50 niches, so the full list of a large account needs several calls.get_niche_keywordsUse this when the user asks about keywords, search terms, or search volume for a niche. Retrieves the master keyword list for the specified Niche — the relevant search terms monitored for ranking and performance metrics. For each keyword, returns search volume, relevancy (numeric score or "Outlier"), and competitor ASIN organic ranks (asinRanks: { ASIN -> rank | null }), plus `origin`: `mkl` (found by the dive), `manual` (added by hand with `add_niche_keywords`), `outlier` / `residue` (moved in from those lists). Only `manual`, `outlier` and `residue` keywords can be taken out with `remove_niche_keywords`. Keywords hidden by the niche's keyword exclusions are not listed; see `list_keyword_exclusions`. Also returns the latestResearchDate.list_keyword_exclusionsUse this to see which keywords are hidden from a niche's Master Keyword List, e.g. when a keyword the user expects is missing from `get_niche_keywords`. Returns the same lists the DataDive web app shows, oldest first: `exact` — each entry hides the one keyword that matches it exactly, with that keyword's `searchVolume` (0 when the niche has no such keyword); `phrase` — each entry hides every keyword that contains the phrase, with `excludedKeywordsCount` and the total `searchVolume` of the keywords it hides (not counting ones already excluded exactly). Exclusions hide keywords wherever they come from: the dive, the Outliers and Residue lists, and hand-added ones. Change them with `add_keyword_exclusions` and `remove_keyword_exclusions`.get_niche_rootsUse this when the user wants to find the highest-impact words across a niche's keywords, asks about 'keyword roots', or wants to prioritize terms for a listing. Retrieves the keyword lexical roots for the Niche — individual words or word-combinations extracted from the Master Keyword List (e.g. 'bluetooth headphones' yields roots 'bluetooth', 'headphones', 'bluetooth headphones'). Returns `roots` and `normalizedRoots` tables, each item with root, frequency (how many keywords contain it), broadSearchVolume (summed search volume of those keywords), and broadSearchVolumeRatio (0-1, relative to the top root), plus the per-keyword breakdowns and latestResearchDate.get_niche_competitorsUse this for competitor ASINs, product titles, BSR, sales/revenue benchmarks, or niche opportunity scoring. Retrieves the list of Competitors within the specified Niche along with Niche statistics. For the Niche: keyword statistics, opportunity evaluation, benchmark median values, and overall competitor strength assessment. For each Competitor: ASIN, product title, BSR, category and full category tree, sales, revenue, ratings, reviews, price, number of variations, image URL, total Ranking Juice, and ranking data. BSR supports ranking Competitors by sales position within mentioned category. For the Ranking Juice breakdown by title, bullets and description, use `get_ranking_juice`.get_ranking_juiceUse this when the user asks 'how do I rank higher', 'what's my ranking juice', or wants listing-optimization guidance. Retrieves the Ranking Juices for each Competitor within the specified Niche. Ranking Juice is DataDive's proprietary metric identifying the key factors driving search-ranking success for each Competitor's listing. Returns currentListing and optimizedListing breakdowns (rankingJuice + per-property contributions: title, bullets, description) plus per-competitor listing scores and the latestResearchDate.list_rank_radarsUse this to find a `rankRadarId` before calling `get_rank_radar_data`. Filter by `nicheId` if the user has already identified a niche. Retrieves a paginated list of Rank Radars — keyword-rank trackers monitoring organic and sponsored positions for specific ASINs over time. Each item includes id, status (ACTIVE, PAUSED or ARCHIVED), asin, marketplace, keywordCount, title, imageUrl, and summary metrics: top10KW, top10SV, top50KW, top50SV. Supports pagination metadata (currentPage, pageSize, total, lastPage, hasNext, hasPrev); a page holds at most 50 Rank Radars, so a large account needs several calls.get_rank_radar_dataUse this to analyze keyword ranking trends over time. Requires startDate and endDate (yyyy-mm-dd), at most 90 days apart. Retrieves historical keyword ranking data for the specified Rank Radar within the date range. Without `currentPage` and `pageSize` it returns every active keyword in one result. To read one page instead — faster for large Rank Radars — pass `currentPage` and/or `pageSize` (max 100) and continue with `currentPage` + 1 while `hasNext` is true. The response carries currentPage, pageSize, total, lastPage, hasNext and hasPrev; `total` is the Rank Radar's active keyword count. Paused keywords are not included. Each keyword has id, keyword, searchVolume, relevancy, ranks (per-day { date, organicRank, sponsoredRank, impressionRank }), and `highlights` — the user tags on this keyword. Each `highlights` entry is the same object `list_rank_radar_tags` returns (id, title, color, description, startAt, endAt, type, krtId, krtKeywordId); its `id` is the `tagId` the tag-management tools take. A rank of 101 means the product was not in the top 100 results that day. For PPC metrics use `get_rank_radar_ppc_data`; for Search Query Performance use `get_rank_radar_sqp_data`. Use after `list_rank_radars` to discover a `rankRadarId`.get_rank_radar_sqp_dataUse this when the user asks how shoppers search, click, add to cart and buy for the keywords of a Rank Radar — Amazon's Search Query Performance (SQP) data, from Brand Analytics. Requires startDate and endDate (yyyy-mm-dd), at most 90 days apart; 30 days or less keeps it fast. Each keyword's metrics are aggregated over the range: searchQueryVolume and searchQueryScore; impressions, clicks, cart adds and purchases, each as the total across all sellers (`*TotalCount`), this ASIN family's count (`*AsinCount`) and its share (`*AsinShare`); click, cart-add and purchase rates; and ctr/cvr for the market (`*Total`) and for this ASIN family (`*Asin`). `numberOfDaysWithData` says how many days of the range had SQP data; metrics are null when there is none, which is normal for low-volume keywords, recent dates (Amazon publishes SQP with a delay) and sellers without Brand Analytics. Results are paged by keyword: `data` holds one page, and the response carries currentPage, pageSize, total, lastPage, hasNext and hasPrev. `total` is the Rank Radar's active keyword count; to read every keyword, call again with `currentPage` + 1 while `hasNext` is true, using `pageSize` 100 for large Rank Radars. Paused keywords are not included. Each call counts toward API usage and is rate limited (about 60 requests/minute). Use after `list_rank_radars` to discover a `rankRadarId`.get_rank_radar_ppc_dataUse this when the user asks about advertising (Sponsored Products) performance for the keywords of a Rank Radar. Requires startDate and endDate (yyyy-mm-dd), at most 90 days apart; 30 days or less keeps it fast. Each keyword's metrics are aggregated over the range: sponsoredRank (median; 101 means not in the top 100 sponsored results), impressionRank and impressionRankShare; how many exact, phrase, broad and auto campaigns target it; organicSales, ppcSales, ppcSpend, costPerClicks, clickThroughRate, conversionRate, totalClicks, totalImpressions, totalOrders and acos. Metrics are null or 0 when the seller runs no ads on a keyword. Set `includeCampaigns` for the per-campaign breakdown. Results are paged by keyword: `data` holds one page, and the response carries currentPage, pageSize, total, lastPage, hasNext and hasPrev. `total` is the Rank Radar's active keyword count; to read every keyword, call again with `currentPage` + 1 while `hasNext` is true, using `pageSize` 100 for large Rank Radars. Paused keywords are not included. Each call counts toward API usage and is rate limited (about 60 requests/minute). For the seller's campaigns as a whole, use `list_ppc_campaigns`. Use after `list_rank_radars` to discover a `rankRadarId`.list_rank_radar_tagsUse this to find a `tagId` before calling `update_rank_radar_tag`, `delete_rank_radar_tag`, `add_rank_radar_tag_search_terms` or `remove_rank_radar_tag_search_terms`. Returns the user tags ("highlights") on the specified Rank Radar, ordered by title (case-insensitive, ascending). Each row carries `id`, `title`, `color`, `description`, `startAt`, `endAt`, `createdAt`, and `keywordCount` — the number of Rank Radar keywords this tag is applied to. The system "paused" tag (the one the quota pauser writes with a reserved colour) is not listed and cannot be addressed from these tools. Supports pagination metadata (currentPage, pageSize, total, lastPage, hasNext, hasPrev); a page holds at most 50 tags.create_rank_radarUse this to start tracking organic and sponsored keyword rankings for an ASIN within a niche. ⚠️ Spends Search Term tokens (cost scales with `numberOfKeywords`) and cannot be undone — set `confirm: true` only after the user approves the cost. Not safe to retry: each call spends tokens again and creates a separate Rank Radar — if a call errors or times out, check `list_rank_radars` instead of re-calling. The first call previews the creation and may return `warnings` alongside the cost note — for example that this product family is already tracked by another Rank Radar. Show every warning `message` to the user verbatim, before asking them to confirm; do not summarise it or decide on their behalf. A warning never blocks creation. Returns the new `rankRadarId`; read its data later with `get_rank_radar_data`. Requires `asin`, `numberOfKeywords` (min 1), and a `nicheId` from `list_niches`.- +31 more on the listing page
BoostedTravel tools 14
search_flightsSearch hundreds of airlines for live flight prices — completely FREE, unlimited, read-only. Returns structured offers with prices, airlines, times, durations, and stopovers. Some offers carry `starlink` for in-flight Starlink Wi-Fi: "confirmed_all" / "confirmed_some" mean the carrier has FULLY fitted that aircraft type, "likely_all" / "likely_some" mean the rollout on that type is underway but incomplete. State only "confirmed_*" as fact; describe "likely_*" as "the airline is fitting this aircraft type, not guaranteed on your flight". Anything ending in "_some" has at least one leg WITHOUT it. An absent field means no information, NOT an absence of Wi-Fi. Covers airlines across all continents including low-cost carriers. Search is async: this tool polls for you, including waiting out the late split-ticket merge. Some offers are SPLIT TICKETS: two separately-issued tickets through a hub, each leg booked from whatever is cheapest for it (usually two different airlines), because no one seller offers the combination as a single ticket. They carry `split_ticket: "true"`, `combo_type: "virtual_interlining"` and `self_transfer: "unprotected"`. ALWAYS tell the user when an offer is a split ticket and what unprotected means: the tickets are not linked, so if the first flight is late and the connection is missed, the second airline owes nothing — no rebooking, no refund. Never present a split ticket as though it were one through-fare. Requires LETSFG_BEARER_TOKEN or LETSFG_API_KEY. See letsfg://guide resource for the full authenticate->search->book workflow.resolve_locationConvert a city/airport name to IATA codes. Always call before search_flights if you only have a city name. Read-only, safe to call multiple times.unlock_flight_offer[Developer API only] Confirm live price with the airline and reserve the offer for 30 minutes. NOT part of the agent flow and NOT needed before book_flight. It requires LETSFG_API_KEY (the paid, prepaid Developer API) and refuses to run on a Bearer token, because the PFS unlock endpoint does not exist — calling it that way used to 404. If you authenticated with `letsfg auth`, go straight from search_flights to book_flight. Requires a Developer API key. Legacy path — not idempotent.book_flightBook a flight from a search result. FLOW: authenticate (once) -> search_flights -> book_flight CHARGES: nothing from LetsFG. A completed booking pays the airline prices from airlines and the major booking sites. RESULT: either {"booked": true, "order_id": "..."} or {"booked": false, "booking_url": "..."} — the second means the booking genuinely did not complete and nothing was charged. That is a normal outcome, NOT a transient error: do not retry, give the user the booking_url. SAFETY: use REAL passenger details — names must match passport, email receives the e-ticket.get_flight_bookingPoll a flight booking started by book_flight. REQUIRED to learn the outcome: on a PFS Bearer token book_flight returns a booking_ref and state "booking_in_progress", not a PNR - the booking itself takes 4-11 minutes. Call it every 20-30 s with that booking_ref until state is terminal: completed -> PNR issued, card charged failed -> the hold was released, nothing was charged needs_attention -> a human is looking at it; do NOT rebook Do not rebook while the state is still moving, and do not treat a slow poll as a failure - the money is HELD, not taken, until the airline confirms. Refs last one hour past the booking start.resolve_hotel_cityConvert a place name to the supplier city id that search_hotels needs. Always call this first if you only have a city name. Read-only and safe to repeat. Use `Id` from the first result as city_id and `Name` as city_name.search_hotelsSearch real, bookable hotel inventory. Requires a payment method on file — the SAME card that authorises flight booking. That applies to search too, not just booking, because a search opens a real session at the supplier. Only free-cancellation, pay-later rates are returned, so everything you see can actually be booked on these terms. The result set is smaller than a metasearch and that is deliberate. `price` is what the guest pays. Keep `session_id` and the chosen offer's `combination_id_v2` — together they identify that exact rate, and book_hotel needs both. Takes up to a few minutes.book_hotelBook one hotel rate. Charges 5% of the price to the card on file immediately as a NON-REFUNDABLE reservation fee; the balance is paid directly to the supplier through the pay link we return, by balance_due_by (the supplier's own auto-cancellation date). Returns a booking_job_id, NOT the booking — a booking takes minutes. Poll get_hotel_booking until status is succeeded or failed. The fee is charged BEFORE the room is committed, so a declined card costs nothing: no reservation exists and nothing is charged. Send expected_price and expected_balance back exactly as search returned them. NOT idempotent — calling twice for the same rate books the room twice and charges two fees.get_hotel_bookingCollect the result of a booking started with book_hotel. Poll every ~20s. status is in_progress, succeeded or failed. On success you get confirmation, reservation_fee_charged, pay_link, balance_due, balance_due_by and the full cancellation ladder. Read-only and safe to repeat.cancel_hotel_bookingRelease a hotel reservation. Free until balance_due_by; after that the hotel's own ladder applies and can reach 100%. The ladder is in the booking terms, so check the cost first. The 5% reservation fee is NOT refunded. Takes over a minute; if it times out do NOT assume it failed — re-check before retrying.authenticateExplain how to connect a card so this server can search and book. Nothing is charged to connect — a 0.00 Revolut setup that saves the card so a booking can be charged later. Call with no arguments. It returns the current instructions and add_card_url (https://letsfg.co/connect). A PERSON must approve once in a browser — there is no endpoint that mints a token from card details, so do not ask the user for card numbers and do not try to automate this step. Two ways in: (a) add LetsFG as a connector in an assistant that supports remote MCP servers and approve it, or (b) any OAuth-capable client can register itself — see https://letsfg.co/for-agents, section "Option B". Both land on the same card screen. RETIRED 2026-09-02: the Stripe lanes (setup_url, setup_session_id, payment_method_id, card_token) and every token they issued. Passing them now fails. This does NOT create a Developer API billing account. Do not use setup_payment for this.setup_payment[Developer API only — you almost certainly want `authenticate` instead] Attaches a card to a PAID prepaid Developer API account. Refuses to run unless LETSFG_API_KEY is set, because agents kept calling this and creating billing accounts they did not need.- +2 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
DataDive
{
"mcpServers": {
"datadive": {
"command": "npx",
"args": [
"-y",
"@datadive-tools/mcp"
],
"env": {
"DATADIVE_API_KEY": "YOUR_DATADIVE_API_KEY_HERE"
}
}
}
}
BoostedTravel
{
"mcpServers": {
"boostedtravel": {
"command": "npx",
"args": [
"-y",
"letsfg-mcp"
],
"env": {
"LETSFG_BEARER_TOKEN": "YOUR_LETSFG_BEARER_TOKEN_HERE",
"LETSFG_API_KEY": "YOUR_LETSFG_API_KEY_HERE"
}
}
}
}
Frequently asked questions
DataDive is categorized under E-Commerce and uses a local stdio subprocess. BoostedTravel belongs to Travel & Transportation and uses a local stdio subprocess. Pick DataDive for e-commerce work and BoostedTravel for travel & transportation.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
DataDive has no declared pricing — check the project's own site. BoostedTravel is listed as free. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add datadive and boostedtravel as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, DataDive has a quality signal of 63/100 (Good) with 1 views, 0 installs and 1 GitHub stars. BoostedTravel has 72/100 (Great) with 9 views, 1 installs and 2,189 GitHub stars.
