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741,830 tools. Updated 2026-11-04 09:25

"A search engine for finding information online" matching MCP tools:

  • Web search, online retrieval, real-time information query, search engine search, Reddit and other community platform discussions, external site posts and trending topics. Trigger when users need to search for the latest information online, look up recent news or trends, query real-time data, research topics via search engines, browse Reddit or community discussions, discover external site posts and trending topics, obtain any online content, web search, online lookup, real-time information, news search, Reddit, trending topics, search engine. Even if the user does not explicitly say "search", trigger this skill whenever their intent involves obtaining real-time web information or verifying current facts.
    ConnectorOAuth
  • Web search, online retrieval, real-time information query, search engine search, Reddit and other community platform discussions, external site posts and trending topics. Trigger when users need to search for the latest information online, look up recent news or trends, query real-time data, research topics via search engines, browse Reddit or community discussions, discover external site posts and trending topics, obtain any online content, web search, online lookup, real-time information, news search, Reddit, trending topics, search engine. Even if the user does not explicitly say "search", trigger this skill whenever their intent involves obtaining real-time web information or verifying current facts.
    ConnectorOAuth
  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Get the stored day-by-day ranking history for one keyword on one search engine over a date range. Reads RankParse snapshots synced on a schedule; it is not a live SERP check. History is inherently single-engine, so engine is required (use get_keyword_rankings first to compare across engines). Days with no synced data are simply absent from rows rather than filled with a zero or placeholder value -- do not treat a missing date as "not ranking". Bing and Yandex are opt-in and lower-frequency than Google; their responses may report availability as provider_limited, meaning that provider did not return enough data for that day rather than the keyword ranking nowhere.
    ConnectorOAuth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    Exposes a standardized web search tool via Brave Search for MCP clients like Codex, Claude, and Cursor, returning stable JSON.
    MIT

Matching MCP Connectors

  • Hybrid sparse-dense neural search with cross-encoder re-ranking and semantic retrieval over streamable HTTP.

  • Your saved places, trips and travel plans — see them, plan days, and add to them from your AI.

  • Look up a NUCC provider taxonomy code (the specialty codes used on HIPAA transactions + NPI registrations) or search by keyword. Returns classification + type + optional specialization. Source: NUCC Health Care Provider Taxonomy Code Set (public; CMS-accepted). WHEN TO USE: Resolving a NUCC provider taxonomy code to its specialty description. WHEN NOT: For finding a provider by specialty in a region (not yet implemented).
    ConnectorNo auth
  • Returns the plain-language meaning and step-by-step fix for one Malinois finding. Use it while helping the user fix an issue reported by scan_app, or when they ask what a finding means. Pass the rule_id exactly as scan_app returned it. Read-only, no network, instant.
    ConnectorNo auth
  • Save a template’s draft. Both kinds take structured `content` — see create_document_template for the node format; notifications use its EMAIL profile (no image, no pageBreak) — or, for a template still on the legacy HTML engine (check get_template_draft’s `engine`), a `body`; a structured draft refuses body-only writes. Notifications also take subject and recipients; documents also take `settings`. Editing a live template’s draft does not change what sends until publish_template. A document on the SVG facsimile engine (engine "SVG") is edited with edit_svg_template, never here. Requires notification:write or document:write.
    Connector
    Destructive
    API key
  • Search for products available in the German dm-drogerie market (online and local stores). USE WHEN: searching dm-drogerie products by name, category, ingredient, property, or any natural language query (any language supported). Often answers questions about ingredients and properties directly. Covers: dm-drogerie markt brands, make-up, skincare, perfume, hair, health, nutrition, baby & child, household, home & living, photo, and pets. OUTPUT: Returns a maximum of 15 products. GTIN, DAN, brand, title, details, category, price, appLink (direct product URL), description, highlights/USPs, and extensive attributes including: - Dietary/Allergen: vegan, vegetarian, bio, glutenFree, lactoseFree, sugarFree, nutFree, soyFree - Cosmetic Ingredients: fragranceFree, alcoholFree, parabenFree, sulfateFree, preservativeFree, dyeFree, oilFree, siliconeFree, naturalCosmetics - Product Properties: waterproof, new, limitedEdition, sellout, onlineOnly, exclusiveDm, dmBrand, purchasable NOT FOR: nutritional information (calories, protein, carbs, fats), complete allergen lists, full ingredient details. For these, use 'getProductDetails' tool with the GTINs or DANs. LIMITATIONS: Only make claims based on EXPLICITLY stated product highlights/descriptions. Do NOT extrapolate or assume properties not mentioned in the results.
    ConnectorNo auth
  • 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.
    ConnectorNo auth
  • Engine version, API contract number, and health. Free (not quota-counted). Call once at the start of a session to confirm the engine is reachable and which contract it serves.
    ConnectorNo auth
  • Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.
    ConnectorNo auth
  • Return the directory's current totals and breakdowns: how many studios are listed, and how they split by country, region, service, engine, platform and team size. Use for any "how many studios..." or "which country has the most..." question, and quote these figures rather than counting search results yourself — they are recomputed from the live database and the counts move.
    ConnectorNo auth
  • Full-text search across all SEC EDGAR filings since 2001 for a keyword or phrase. Wraps EDGAR's own full-text search index, so it covers every filer and form type, not just a single company. Useful for finding who is disclosing a particular risk, technology, litigation, or event across the entire market. When to use: cross-company research ("who is disclosing AI-related risk factors"), finding filings that mention a specific term, litigation or regulatory tracking. When NOT to use: you already know the company (use edgar_filings_feed, which is company-scoped and cheaper), or you need results from before 2001 (EDGAR full-text search does not cover that far back). Args: - query (string, required): search text. Wrap an exact phrase in double quotes, e.g. "\"material weakness\"". - forms (string[], optional): restrict to form types, e.g. ["10-K"]. - dateFrom (string, optional): ISO start date (YYYY-MM-DD). - dateTo (string, optional): ISO end date (YYYY-MM-DD). - limit (integer, optional, default 10): maximum hits to return (1-50). Returns structuredContent: { "query": "material weakness", "totalMatches": 10000, "totalIsApproximate": true, "count": 2, "hits": [ { "id": "0001193125-26-123456:doc.htm", "entity": "Example Corp.", "form": "10-K", "filedAt": "2026-03-01", "cik": "0000320193" } ], "source": "https://www.sec.gov/edgar" } "totalMatches" is a lower bound and "totalIsApproximate" is true once EDGAR's own count exceeds its display cap (10,000) — narrow with forms/dateFrom/dateTo for a precise count.
    ConnectorNo auth
  • The Search Console and Bing Webmaster properties the workspace's connected accounts can read. The first console call; every other console tool takes a property from here. Use when: "what sites are in my Search Console", before any console_get_* call, or to check which engine is connected. Not for: third-party sites the user does not own, use seo_get_domain_overview. Live rankings, use seo_get_serp. Returns: List. rows[]: engine (google | bing), property (the id to pass on: sc-domain:example.com, https://example.com/ or a Bing site URL), permission (Google: siteOwner, siteFullUser, siteRestrictedUser, siteUnverifiedUser; Bing: null), verified. NotConnected when no account of that engine is connected; its connect_url is where the user connects one. Cost: 0 credits. The user's own data is free; 60 console calls per minute per workspace. Cached 1 hour. Example: {"engine": "all"}
    ConnectorAPI key
  • The sitemaps submitted for one of the user's properties, with when they were read, how many URLs they carry and their errors. Use when: "is my sitemap picked up", "how many URLs did Google read from the sitemap", checking a submission after a site change. Not for: submitting or resubmitting one, use console_submit_sitemap. Whether one URL is indexed, use console_inspect_url. Finding pages a sitemap misses, use seo_run_technical_crawl. Returns: List. rows[]: path, type, submitted_at, last_read_at, pending, is_index, urls_submitted, urls_indexed (Google reports 0 today), warnings, errors. null = the engine does not say. Cost: 0 credits. Cached 10 minutes. Example: {"property": "https://www.example.com/"}
    ConnectorAPI key
  • TikTok videos matching a keyword, ranked by the platform's own search. Use when: "what is TikTok saying about X", finding creators in a category, watching a product or a brand name. Not for: one account's own videos, use tiktok_get_videos. A complete window of everything posted (TikTok search is ranked and never complete). Returns: List, ranked. rows[]: videos with author and author_followers, created_at, text (cut at 2000 characters), likes, comments, shares, saves, views, media, duration_s, links, transcript and top_comments[]. saves is how many people saved it, music the sound, and author_followers sizes each creator without another call. null or empty = the platform does not publish it. Cost: 1 credit per page. Cached 6 hours. Example: {"query": "creatine gummies", "since": "month", "sort": "popular"}
    ConnectorAPI key
  • Monthly Amazon search volume for up to 1,000 keywords you already have, in the order given. Use when: "how many people search Amazon for X", comparing Amazon demand with Google demand, sizing a product idea on Amazon. Not for: Google volume, use seo_get_keyword_metrics. Finding keywords, use amazon_search_keywords. Returns: List. rows[]: keyword, volume (monthly Amazon searches; null = no data). Cost: 5 + 5 per 100 keywords. 10 keywords = 6 credits. Cached 7 days. Example: {"keywords": ["standing desk", "desk converter"]}
    ConnectorAPI key
  • Look up the Final POS REST API (https://api.finalpos.com) — endpoint method/path, request fields, response shape, and a worked fetch example. This is the ONLINE-ONLY fallback for admin/management operations command-frame cannot express (creating products/variants/categories, customer management, outlets/stations/tax tables, webhooks). Command-frame is ALWAYS first choice for live POS data — it works offline and the host owns money/totals. A call to this API is network egress from the station: it fails whenever connectivity does, so never put one in the sale path — use it for setup/admin work and degrade gracefully. Pass resource to list a domain, operation for one endpoint, or query for fuzzy search.
    ConnectorOAuth
  • List security/safety findings for your workspace, most recent first. Optionally filter by status, target model, minimum severity, or a specific run. Returns a compact summary; call get_finding for the repro detail of any one finding. On a plan that withholds a finding's proof, category reads '[redacted]' and get_finding returns the same — the finding and its severity are real, the evidence is withheld. Paginated: 200 findings per page (max 200). The result carries total_matched and, when there is more, next_cursor: pass it back as 'cursor' with the same filters (it is bound to them) to read the next page, until it is absent.
    ConnectorOAuth