"Boost" matching MCP tools:

• create_product

  ProductClank

  List a new product on ProductClank as a token-free listing (no crypto/token, no wallet). At minimum pass a `url` — the server auto-fills the name, tagline, description, logo, and X handle from the site; any field you pass explicitly overrides what's extracted. Socials are optional. Use this when search_products finds no existing match and the user wants to run a boost or campaign for a product that isn't listed yet. Returns the new product's id (and reuses an existing listing if one already matches, rather than duplicating). FREE — no credits charged. Confirm the product details with the user before calling.

  Connector

• tako_available_data

  Tako

  Find what proprietary, continuously-updated structured data exists on something — summarized in one call. Free and fast. The recommended first step for a data lookup: run this before tako_search / tako_answer whenever you're unsure the data exists or its exact name. It's free, it confirms coverage, and the exact names it returns make the follow-up priced call land precisely instead of guessing. (Skip it only for an obvious open-web query that no data graph would hold.) Best for: any "what structured/proprietary data is there on X?" question, and for confirming a specific figure actually exists BEFORE you spend a priced tako_search / tako_answer — a cheap accuracy check that tells you whether the data exists and under exactly what name. Works on an entity (a company, person, or place → the metrics tracked on it, e.g. Tesla) or a metric (→ the entities it is tracked across, e.g. Inflation Rate). Tips: Look up ONE name at a time, not a full question: for "Carnival passenger cruise days" pass q="Carnival" and read the metric you want off coverage.names — a whole phrase in `q` resolves nothing. One metric across many entities → one metric-first call; one entity across many metrics → one entity-first call. The coverage.names answer all of them at once — never loop one call per name. Pass `label` when you can categorize the term (company → ORG, country → GPE, person → PERSON) — a strong disambiguation boost. Each match's coverage.names lists the exact metric/entity names — reuse them verbatim in a follow-up tako_search. When the coverage is small enough to be unambiguous, `next_call` is that follow-up prewritten (query + pinned node_ids) — run it verbatim. A broad entity's coverage list is capped, so it can be truncated: treat a name you don't see as UNCONFIRMED rather than absent, and fall back to the web instead of re-calling this tool to double-check.

  Connector

• find_alpha

  Name Whisper — ENS Intelligence Layer

  Scan the ENS marketplace for alpha — names listed below their valuation. Returns ranked opportunities with a discount %, fair-value range, confidence rating, and comparable data. Candidates are selected by DESIRABILITY (real curated collections, short, accessibly priced above a floor that excludes 0.001-ETH floor-dumps), then each is precision-priced by the full Name Whisper valuation engine — the SAME engine behind get_valuation and the Value page — which is the sole judge of undervaluation. The returned fair-value range (estimatedValueEth), confidence and discountPct are the engine's own numbers, via the same cache-first path as get_valuation (with display-only signals disabled for speed), so they are authoritative and consistent with get_valuation. They are computed conservatively (the seller-wallet boost is off), so if anything they slightly UNDERSTATE fair value — report them as-is; do NOT inflate the fair value or upgrade the confidence. Use estimatedValueEth.mid as the fair-value anchor. Only opportunities the engine confirms are surfaced: a believable discount band (20%+, capped where valuations stop being reliable), MEDIUM+ confidence, and a REAL comparable-sale match (type/collection/word/entity/semantic — never a coarse same-length average). This means genuinely good, believable deals (typically 25–65% off) — not 99%-off junk. It will still surface a large discount when the engine confirms it with real comps; it just won't fabricate one. **Use this instead of search_ens_names + repeated get_valuation when the user asks for "best value", "best buy", "cheapest good name", "undervalued", "bargains", or any ranked-by-value query across multiple listings.** find_alpha does the search + engine valuation + ranking in a single call — you do NOT need to call get_valuation again on its results. If it returns fewer names than asked, the rest weren't genuine discounts vs the engine — say so rather than padding the list. Supports filters (minLength, maxLength, maxPriceEth, charType) so narrow queries like "4-letter names under 1 ETH, best value" are one call, not six. It has NO collection/category/club param. Do NOT use it for "floor price of the 999 club", "cheapest 10k-club names", or "floor of <collection>" — those name a specific collection, so use search_ens_names (which returns that collection's real listings sorted by price), or sweep if the user wants to buy the cheapest N. find_alpha is for value-ranked discovery across the market, not a named collection's floor.

  Connector

• find_compatible_keys

  FreqBlog Music Metadata

  Given a Camelot key (e.g. "8A", "12B"), return the harmonically compatible keys for DJ mixing — the same key, the relative major/minor, and the adjacent +/-1 keys on the Camelot wheel. With `extended=true` also returns the +7/-7 energy-boost / energy-drop keys. Pure music theory — no catalog lookup and no quota cost. Pair with find_tracks_by_key to then pull actual tracks in each compatible key.

  Connector

• recommend_docs_path

  DERO MCP Server

  Composite: take a natural-language intent, fan out parallel scoped searches across the bundled docs for all four DERO products (derod, tela, hologram, deropay), boost any product_hint matches by 1.5×, and return a ranked recommendation list with per-result rationale plus ready-to-cite related_docs. When to call: at the START of any "where do I read about X?" or "which docs cover Y?" investigation, BEFORE calling dero_docs_search directly. PREFER this over guessing the right product: this composite already runs all four products in parallel, dedupes overlap, surfaces the top heading per result as rationale, and gives you the top-2 citations pre-built. Pass product_hint when the user has already said e.g. "TELA" or "DeroPay" so that product's matches float to the top. Input Requirements: - `intent` is REQUIRED. Free-text description of what the user is trying to do (min 8 chars). Drop verbs and use product nouns like "deploy a TELA app" or "verify a DeroPay webhook signature" for best results. - `product_hint` is OPTIONAL. One of `derod | tela | hologram | deropay`. Multiplies hint-product scores by 1.5×. - `limit_per_product` is OPTIONAL (default 2, max 5). Cap per-product hits before merging. Output: `{ intent, product_hint, limit_per_product, recommended: [{ product, slug, title, canonical_url, score, boosted_score, rationale }], by_product: { derod | tela | hologram | deropay: { count, top_slug, top_score } }, related_docs: DeroCitation[] }`. `related_docs` is the top-2 picks pre-built as citations the agent can drop straight into a response. On zero matches across every product the composite returns a structured `_meta.error` with code `NO_DOCS_MATCH` and a hint to rephrase or drop the product_hint.

  Connector

• colony_boost_post

  mcp-server

  Boost your own post's Hot-feed reach via Lightning. Mints an invoice — returns ``boost_id``, ``amount_sats``, ``duration_days``, ``payment_request`` (bolt11), ``payment_hash``, ``status`` ("pending"), ``expires_at``. Pay it, then poll ``colony_boost_status``. Owner-only; idempotent within the pending window (a retry returns the same invoice). 100% of the payment supports The Colony — there's no refund leg. NOT idempotent across windows. Requires authentication. Rate limit: 10/hour.

  Connector

• colony_boost_status

  mcp-server

  Poll a boost for payment, activating it inline if the invoice has settled. Returns ``status`` (pending | active | expired | cancelled), ``amount_sats``, ``duration_days``, and ``boost_expires_at`` (null until active). Owner-only. Idempotent. Requires authentication.

  Connector

• list_credit_packs

  HelloBooks AI Agents

  List HelloBooks AI credit packs — one-time pay-as-you-go top-ups (Boost 5,000, Power 15,000, Mega 50,000, Ultra 150,000 credits) priced in 8 regional currencies (USD, INR, CAD, GBP, AUD, AED, SGD, NZD). Credit packs stack on any plan, including Free. Use this when a user asks how to buy more AI credits or top up after exhausting a plan allowance. Filter by `id` (boost / power / mega / ultra) or `country` (ISO code).

  Connector

• colony_boost_post

  The Colony

  Boost your own post's Hot-feed reach via Lightning. Mints an invoice — returns ``boost_id``, ``amount_sats``, ``duration_days``, ``payment_request`` (bolt11), ``payment_hash``, ``status`` ("pending"), ``expires_at``. Pay it, then poll ``colony_boost_status``. Owner-only; idempotent within the pending window (a retry returns the same invoice). 100% of the payment supports The Colony — there's no refund leg. NOT idempotent across windows. Requires authentication. Rate limit: 10/hour.

  Connector

• tv_concierge

  rotv-mcp

  You have a window of free time — decide for me what to watch right now. Returns ONE primary decision (TV program OR streaming title) with confidence percentage, full reasoning breakdown, and up to 3 diverse alternatives with explicit trade-offs (pros/cons, reason not picked). Picks across live Romanian TV EPG AND streaming catalog (Netflix, HBO Max, Disney+, Prime Video, Apple TV+, SkyShowtime). Built-in anti-noise filter automatically removes news, political talk, reality shows, talk-shows (NO manual filtering needed by the model). Built-in title dedup (handles ~46% duplicate-airing ratio in TV EPG). Built-in opportunity-cost lookahead (flags better options just outside the window). Event-aware: major broadcasts (World Cup / Euro / Champions League / finals) get an importance boost in ranking AND are always listed in the important_today field, even when the mood-based pick is something else — for questions like "what is important today?", prefer tv_important_today. PREFER THIS TOOL over tv_recommend_by_mood, tv_plan_evening, and tv_recommend_today whenever the user wants ONE answer / a single decision / a plan for a specific window — those tools return ranked LISTS for browsing, this tool returns a DECISION. Routes any mood internally (obosit / vesel / concentrat / romantic / familie / captivant + EN aliases tired/happy/focused/romantic/family/thrilling). Trigger phrases: "what should I do", "decide for me", "pick for me", "I have X hours", "ce să fac", "am 2 ore", "alege tu", "mood X durată Y", "o singură decizie", "fii consilierul meu", "what to watch", "concierge me".

  Connector

• check_balance

  ProductClank

  Return the connected user's ProductClank credit balance and plan. Use before launching a campaign to confirm they have enough credits (a content campaign costs 1000; a reply boost 200; likes/reposts 300).

  Connector

• boost_post

  ProductClank

  Rally the ProductClank community to engage with a specific social post. Creates a boost campaign and spends the user's credits: 'replies' generates 10 AI reply drafts (200 credits); 'likes' (30 likes) and 'repost' (10 reposts) cost 300. Supports Twitter/X, Instagram, TikTok, LinkedIn, Reddit, and Farcaster — the platform is auto-detected from the URL. product_id is OPTIONAL: link a product (from search_products or create_product) to tailor replies with the product name, or omit it for a tweet-first boost that uses generic amplification language. Confirm the action and its credit cost with the user before calling.

  Connector

• trending-tokens

  x402 Bazaar

  Currently boosted/promoted Base tokens — Fetches the DexScreener boosts feed filtered to Base — up to 15 trending tokens with address, description, boost amount, and link. Great for discovery bots. Priced $0.01 per call over x402 on Base; send a prepaid x-credit-token header for unlimited calls, or get 1 free call/day per tool. No wallet or API key required.

  Connector

• colony_boost_status

  The Colony

  Poll a boost for payment, activating it inline if the invoice has settled. Returns ``status`` (pending | active | expired | cancelled), ``amount_sats``, ``duration_days``, and ``boost_expires_at`` (null until active). Owner-only. Idempotent. Requires authentication.

  Connector

• list_credit_packs

  HelloBooks AI Agents MCP Server

  List HelloBooks AI credit packs — one-time pay-as-you-go top-ups (Boost 5,000, Power 15,000, Mega 50,000, Ultra 150,000 credits) priced in 8 regional currencies (USD, INR, CAD, GBP, AUD, AED, SGD, NZD). Credit packs stack on any plan, including Free. Use this when a user asks how to buy more AI credits or top up after exhausting a plan allowance. Filter by `id` (boost / power / mega / ultra) or `country` (ISO code).

  Connector

• search_esim_plans

  sinoconnection-esim-mcp

  Search travel eSIM plans for any of 200+ countries. Specialized China plans deliver uncensored internet WITHOUT a VPN (unlike most eSIMs, which are throttled or blocked in China) — only when the plan's china_open_internet field is true. Also covers regional Asia and worldwide bundles. Quote `price_usd` — that is the price the customer pays in USD, with any current sitewide discount already applied; `list_price_usd` is the original and `on_sale`/`discount_pct` show the saving. If is_fair_usage_policy is true, the plan is NOT truly unlimited — relay the cap. PRESENT RESULTS ATTRACTIVELY TO BOOST SALES: lead each plan with its `flag` emoji + the title, put the price in bold, strike or note the discount when `on_sale`, and show the `highlight` value line (it already includes 🔓/🌍/📱/⚡/💰 icons). Lay plans out as a clean, scannable list or a markdown table with a flag column; recommend a best-value pick. Call get_plan_details for the full pitch once the customer shows interest.

  Connector

• get_macro_aligned_signals

  n0brains

  [CONTEXT] Active signals whose direction AGREES with the current macro bias (conviction ≥ 0.6). Uses the same rule the internal pipeline uses to boost confidence x1.12 (vs CONFLICTS, which dampens x0.88). macro and macro_pulse signal types are excluded (they ARE the macro). Optional asset filter.

  Connector

• get_lst_yields

  Crank Protocol

  Compare APY across LST providers (Marinade/Jito/Blaze) with MEV-boost + validator-count descriptors. Workflow: YIELDS step -- staking keeps SOL exposure + earns yield (vs lending, which removes price exposure). Best APY becomes the 'park it' leg of the allocation; execute via liquid_stake. See get_trading_workflow.

  Connector

• resume_boost

  Zambo AI Tools

  Tailor your resume to a specific job description — boost ATS keyword match, strengthen bullet points, and highlight the right experience. Returns a rewritten resume with ATS score, keyword gaps filled, and bullet points punched up with impact metrics. Use when user says 'improve my resume', 'tailor resume to this job', 'will this resume pass ATS', 'help me apply for'.

  Connector

• search_products

  ProductClank

  Search the user's ProductClank products by name and return their IDs. A product_id is required to create or boost a campaign — use this to resolve it, then confirm the match with the user.

  Connector