"A server for finding shopping information and deals" matching MCP tools:

• cyanheads_describe

  cyanheads-mcp-server

  Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.

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• pricetik_trending_deals

  mcp-server

  Today's best deals ranked 0-100, across every vertical, with no specific product ("what are the best deals right now?"). `surface`: shopping (default, retail deals by stored score), hotels (biggest 7-day nightly-rate drops), events (activity rate drops), tickets (live-event tickets below their 30-day median, with a reasons[] breakdown), or all (labeled per-surface sections: hotels, things to do, event tickets, shopping). Rows carry a drillDownTool for the next call (hotel_details / activity_details / ticket_details / price_check) and a dealScore. Optional category filter (shopping only) and minDealScore (shopping default 60). URLs are pricetik.com/go/ affiliate redirects — pass to the user's browser unchanged, never fetch server-side. No API key required. For a specific query use pricetik_search.

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• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

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• pricetik_search

  mcp-server

  Discovery search across PriceTik surfaces (shopping/hotels/events) — see the `surface` param for what each value returns. For a SPECIFIC intent prefer the dedicated tool (`pricetik_hotel_search`, `pricetik_activity_search`) for richer, date-accurate results in their own widget; use `pricetik_search` when exploratory or the surface is unknown. For a multi-surface trip ("a hotel AND a show"), do NOT use `surface=all` to commingle — fire parallel dedicated calls or use `pricetik_trip_plan` (includeTickets=true for a ticketed show) / `pricetik_compare_destinations` instead. The events surface also returns a separate labeled "Event tickets" section when live-event tickets match (city, eventDate, a pricetik_ticket_details drill-in); call pricetik_ticket_search directly for ticket-specific city/date filtering. For "best deals right now" with no product in mind use pricetik_trending_deals.

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• semantic_search

  DC Hub — Data Center & Power Intelligence

  Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 21,000+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".

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• semantic_search

  DC Hub — Data Center Intelligence MCP Server

  Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 21,000+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".

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• add_recipe_to_shopping_list

  scraps-kitchen-mcp

  Add all ingredients from a saved recipe to the shopping list. Use when the user wants to shop for a specific recipe. Requires the recipe to have structured ingredient data (most recipes do after enrichment). Get recipe IDs from get_recipes first.

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• remove_shopping_list_item

  scraps-kitchen-mcp

  Permanently remove an item from the shopping list. To remove all checked-off items at once, use clear_checked_shopping_items instead. Get item IDs from get_shopping_list first.

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• clear_checked_shopping_items

  scraps-kitchen-mcp

  Remove all checked-off items from the shopping list at once. Use after a shopping trip when the user has bought everything marked. To remove a single item, use remove_shopping_list_item instead.

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• list_transactions

  DC Hub — Data Center Intelligence MCP Server

  M&A and capital transactions in the data center sector — 2,000+ tracked deals (2019-present), each with its disclosed value where public (many private deals are undisclosed). Returns deal name, buyer, seller, value, date, market, target operator, type (acquisition/JV/refinance/recap). Filter by year, min_value_usd, region, buyer, or target. Try: list_transactions year=2026 min_value_usd=1000000000. Broad M&A and capital-deal flow with filters; do NOT use for hyperscaler-specific lease/PPA/JV activity (use hyperscaler_deals) or a single-deal post-mortem (use deal_autopsy).

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• register_ucp_profile

  UCP Gateway

  Register a public hosted UCP agent profile and receive agent_id/profile_url. Default path: send agent_name plus public_key_jwk and the gateway builds the canonical UCP profile with default Shopping capabilities. Re-registering the same public_key_jwk in the same namespace is idempotent and returns the existing agent_id. Do not build a capability map for normal registration. Create local ./.ucpgateway/ files; keep private_key.jwk local and save returned agent_id/profile_url/profile_json to ./.ucpgateway/agent.json.

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• analyze_win_loss

  StackSwap

  Analyze the user's CLOSED deals (won + lost) to surface which attributes actually predict wins. Computes win rate per attribute value WITH sample size, and ranks attributes by the spread between their best- and worst-converting values — the data version of the win-rate-by-signal motion. By default cuts by source, type, and owner; pass `attributes` to add any field present on the deals (e.g. segment, competitor, size). Values below `minSample` (default 5) are suppressed as noise. Accepts loosely-typed deal records; needs an `outcome` of won/lost (aliases: outcome/status). Returns the ranked attributes with per-value win rates and the reallocation takeaway. Operates only on supplied deals. Use when the user asks 'which sources/signals convert best', 'why are we winning/losing', or pastes closed-won and closed-lost deals.

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• serpapi_google_shopping

  Serpapi

  Search Google Shopping for `<query>` — returns product title, price, source, rating, reviews, product ID, and link via SerpApi. Example: serpapi_google_shopping({ q: "wireless earbuds", gl: "us", hl: "en", _apiKey: "your-serpapi-key" })

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• gtm_signal_act

  Vaaya

  Act on a signal finding — the exit from discovery into the lead repository (VAA-100). action='find_people' (default) runs a paid Exa search (≤5¢) for decision-makers at the finding's company and upserts them into `gtm_leads` with source 'signal' and the signal headline as their hook/why; action='dismiss' marks the finding handled without spending. Both stamp acted_at so a finding is handled once (a second find_people returns already_acted). Pass `finding_id` (from `worker_findings` or the Workers page's buying-signals feed) and optionally `roles` to steer who to look for (default founder/CEO/CTO/Head-of/VP). Returns { ok, action, found, added, charged_cents }.

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• web_search_exa

  exa

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

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• list_transactions

  DC Hub — Data Center & Power Intelligence

  M&A and capital transactions in the data center sector — 2,000+ tracked deals (2019-present), each with its disclosed value where public (many private deals are undisclosed). Returns deal name, buyer, seller, value, date, market, target operator, type (acquisition/JV/refinance/recap). Filter by year, min_value_usd, region, buyer, or target. Try: list_transactions year=2026 min_value_usd=1000000000. Broad M&A and capital-deal flow with filters; do NOT use for hyperscaler-specific lease/PPA/JV activity (use hyperscaler_deals) or a single-deal post-mortem (use deal_autopsy).

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• list_live_deals

  AgentsPrice

  AgentsPrice public live-deals feed (electronics, gaming, home, fashion), cached about 10 minutes, containing only real sourced deals with live buy links. No API key required. Use for a quick read of what is genuinely on sale right now.

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• prioritize_pipeline

  StackSwap

  Rank a set of OPEN DEALS the user brings (from their CRM, a CSV, a warehouse query) by expected value (amount x win%) with a velocity penalty for stalled deals, and bucket them into Work now / Soon / Watch with reasons and risk flags (past close date, no next step, stalled in stage). Accepts loosely-typed deal records — common field aliases (amount/value/acv, stage/dealstage, probability/winProb, closeDate/closeInDays, daysInStage, nextStep) are normalized automatically; win% is inferred from the stage name when absent. Optional `quota` adds a weighted-coverage line; optional `config.stageProbabilities` overrides the stage->win% map. Operates only on supplied deals — it never returns net-new prospects. Use when the user asks 'which deals should my reps work first', 'prioritize my pipeline', or pastes a deal list.

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• audit_pipeline_hygiene

  StackSwap

  Audit the user's OPEN DEALS for data hygiene and return a cleanliness score (0-100) plus the dirty deals ranked by impact (value x severity). Flags: past close date, missing close date, no next step, stalled in stage (beyond `config.staleDaysThreshold`, default 45), missing amount or stage, and win%/stage mismatch. Accepts loosely-typed deal records (amount, stage, closeDate, daysInStage, nextStep, winProb normalized). Returns the score, the most common issues, and the worst offenders. This is the data version of the pipeline-coverage-audit motion — run it before trusting a forecast. Operates only on supplied deals. Use when the user asks 'is my pipeline clean', 'audit my deals', or pastes a deal list.

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• get_ngx_market_overview

  Mansa African Markets

  Get a real-time overview of the Nigerian Stock Exchange (NGX). Returns the All Share Index (ASI), market capitalisation, trading volume, deals, advancers, and decliners. Use this when the user asks about the Nigerian stock market at a high level.

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