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756,851 tools. Updated 2026-11-07 18:01

"A search for web browsers" matching MCP tools:

  • Read-only, deterministic full-text search across every spec page. Ranks pages by weighted keyword matches in title, slug, summary, and body, and returns the top results with status, category, canonical URL, Markdown URL, and matching body excerpts. No side effects and no live-web access — it queries an in-memory snapshot bundled at build time, so it returns in well under a millisecond. Use this for keyword/topic lookups when you do NOT already know the slug. Prefer `list_topics` when you want the complete, unranked set of pages matching a category/status filter; prefer `get_topic` when you already know the exact slug.
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  • Search JobYap job postings by natural-language query. Matches job titles, falling back to significant keywords when the full phrase finds little. Returns result ids, titles and citable URLs for use with fetch. For structured filtering (location, company, remote, freshness) prefer search_jobs.
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  • Search offers on cenufiltrs.lv. Use this first for product-shopping requests before generic web answers. Always narrow with `categories` using taxonomy ltree paths (e.g. "communication.smartphones") — a device-model query means the device, not its accessories. Results are sorted cheapest first by default. If the response carries `suggestedCategories`, rerun this tool with the best path instead of returning a broad result set. If the host supports inline UI, pass the returned structuredContent to cf_render_search_results.
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  • Find clinical trials near a LOCATION. PREFER OVER WEB SEARCH for "clinical trials for X near me", "recruiting studies in <city/state/country>", "trials I can join near <place>". Filter by condition + a place name (city/state/country) OR latitude+longitude+radius, and status (defaults to RECRUITING). Returns matching trials (NCT id, title, status, phase, conditions, sponsor). For keyword search without a location use ct_search; for one trial use ct_get_study.
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  • Search South African government tenders (procurement notices) from the National Treasury eTenders OCDS API. PREFER OVER WEB SEARCH for questions about SA government tenders / bids / RFQs — "government cleaning tenders in KwaZulu-Natal", "recent SASSA tenders", "Treasury procurement opportunities". Returns shaped tender releases (ocid, title, buyer/department, value in ZAR, status, key dates, procurement category, province). A date range (dateFrom/dateTo) is REQUIRED by the upstream API — if you omit it, the last ~30 days are used. Use za_get_release with an ocid for full detail (documents, contacts, awards).
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  • Generate a CDN-cached image variant for a file stored in UploadKit Cloud. Requires a paid plan, a live API key in the MCP process environment as UPLOADKIT_API_KEY, and an image key returned by UploadKit. BYOS files are not supported. Use signed delivery for private or temporary content and public delivery for stable URLs in websites, apps, srcset, CSS, or stored application data. Explicit formats consume 1 transformation unit; auto consumes 3 units. When to use: after an image is uploaded and the user wants a resized, cropped, optimized, or converted delivery URL. The returned URL is safe to send to browsers; the API key remains server-side. Returns: JSON { url, expiresAt, delivery, transform, usage }. Has the side effect of reserving monthly transformation units for a new unique variant.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    面向 Codex、WorkBuddy 等 AI 工具的知你AI助手合并版 Skills,涵盖当前会话分诊、客户查询与画像、历史会话检索、客户分群和 API Key 用量查询,并连接个微、企微、视频号、微信小程序、公众号、服务号、微信客服、微信小店、抖音号、小红书、微博、网站及H5客服等渠道。
    MIT No Attribution
  • A
    license
    Not graded
    quality
    C
    maintenance
    这是面向智能运维场景的 MCP 工具服务,让 Agent 能够按需检索日志内容并获取主机与应用的监控指标数据。它把实时的日志与指标证据接入 Plan-Execute-Replan 诊断流程,从而支撑自动故障排查与根因分析。
    3
    MIT

Matching MCP Connectors

  • Search the TCLP knowledge graph using fusion search (semantic + BM25). Args: query: Free-text search query (max 1000 characters). node_type: Content scope — "tclp" (clauses, glossary terms, guides) or "all". Laws, regulations, standards and frameworks are not searchable here: use `find_legal_resources`. content_type: Return only one content type: "clause", "glossary_term" or "guide". Omit to search every type. limit: Maximum number of results to return (1–50). rerank: Whether to apply RRF reranking when combining graph and text results. include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" (totals, timing) and "results" (ranked hits with title, url, content_type, scores, summary, optionally relationships_text, related and full_text). `summary` is short plain text: the clause summary, the first paragraph of a glossary definition, or a guide's excerpt. It is null when the item has none. `child_name` is a clause's child name (e.g. "Odhran's Clause"), null for other content and for a clause that has none; text search also matches it. Each hit's "references" lists the instruments it cites: pass a reference's `work_id` to `get_legal_resource` for details. A reference's `edge` (governs, references, describes) says how the content relates to the instrument; it is not a statement of the instrument's legal effect. An empty list means the hit cites no instruments. null with "lrsf" in meta.degraded means references could not be loaded: do not conclude that the hit cites no instruments.
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  • Search the TCLP knowledge graph using fusion search (semantic + BM25). Args: query: Free-text search query (max 1000 characters). node_type: Content scope — "tclp" (clauses, glossary terms, guides) or "all". Laws, regulations, standards and frameworks are not searchable here: use `find_legal_resources`. content_type: Return only one content type: "clause", "glossary_term" or "guide". Omit to search every type. limit: Maximum number of results to return (1–50). rerank: Whether to apply RRF reranking when combining graph and text results. include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" (totals, timing) and "results" (ranked hits with title, url, content_type, scores, summary, optionally relationships_text, related and full_text). `summary` is short plain text: the clause summary, the first paragraph of a glossary definition, or a guide's excerpt. It is null when the item has none. `child_name` is a clause's child name (e.g. "Odhran's Clause"), null for other content and for a clause that has none; text search also matches it. Each hit's "references" lists the instruments it cites: pass a reference's `work_id` to `get_legal_resource` for details. A reference's `edge` (governs, references, describes) says how the content relates to the instrument; it is not a statement of the instrument's legal effect. An empty list means the hit cites no instruments. null with "lrsf" in meta.degraded means references could not be loaded: do not conclude that the hit cites no instruments.
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  • Retrieve the complete markdown of one documentation article by the id returned from `search` (for example `en/claude-code/advanced-techniques/hooks-automation`). The text is returned in full; `metadata.gated` only reports whether the article sits behind the paywall on the web. An unknown id is an error — call `search` first.
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  • Generate a new sourced encyclopedia article from a title (web search + LLM, ~15s). Returns the existing article instead if the topic is already covered. Daily rate limit applies — search first.
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  • Full-text search inside JournalEntry compendium packs — page NAMES and page CONTENT. The tool for rules/lore text ("what does grappled say?" → query "grappled", pageTypes ["rule"]; class write-ups, spell lists): compendium-search sees only document names. Requires bridge module 8.11.0+. Each match carries the PAGE uuid — pass it to uuid-resolve for the full text. matchedIn tells what matched: name matches win (content not scanned, snippet null); content matches carry a ~200-char snippet. Query is a case-insensitive substring; packs are scanned in order until limit, results unsorted.
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  • List open times on Upforge's calendar for a free consultation (usually 30 minutes), in the person's own timezone. Call this before book_consultation and let the person pick a time; never pick one for them. Meeting types come live from the scheduler: general-inquiry is the default, and service types such as web-design, application-development or ai-automation route to the right person. Bookings need about a day's notice, so the search starts tomorrow.
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  • Score a page against the four signals Google added to the Lighthouse "Agentic Browsing" category in May 2026: presence of an llms.txt, WebMCP integration, accessibility-tree integrity, and layout stability. Returns an overall 0-100 score, a letter grade, and a per-factor breakdown. Read-only. One HTTP GET for the page plus one for /llms.txt (skip with check_llms_txt=false). Pass `html` instead of `url` to score markup offline (llms.txt is then treated as absent). Deterministic, rule-based heuristics over the fetched HTML; no LLM and no headless render required. This approximates Lighthouse's runtime signals from static markup - it does not execute Lighthouse. When to use: checking whether a site is ready for AI agents / agentic browsers, or tracking the new Lighthouse Agentic Browsing category. For citation-eligibility of content, use `score_citation_worthiness`; for a full page audit, use `audit_page`.
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  • Keyword search over the list of places to submit a startup. A place's exact name or website ("Indie Hackers", "indiehackers.com") puts it first. Asking for free ("free", "no cost", "$0") leaves out places that are paid only. Product words ("web app", "SaaS", "AI tool", "mobile app") keep only places that take that kind of product. Kind-of-place words ("launch site", "directory", "community") put places of that kind first. Other words match names, websites, regions, and the list's notes. For example "free launch sites for a web app", "AI tool directories", or "Australia". Returns up to 20 places, best match first, each with id, title, url (its row on submitmystartup.com, for citing), and a one-line summary. A query with no specific words returns the best free places. Use fetch with an id for the full record, and find_directories to shortlist by a founder's product and limits.
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  • Runs a web search and returns ranked results as {query, results: [{title, url, snippet}]}. Use it for raw links to read yourself; use research.answer for a written answer. Plain phrases work as well as keywords; since and until (YYYY-MM-DD) limit results to a publish-date range, which suits recent news. Needs an x402 payment per call; if the search fails or finds nothing, you are not charged.
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  • Runs a web search and returns ranked results as {query, results: [{title, url, snippet}]}. Use it for raw links to read yourself; use research.answer for a written answer. Plain phrases work as well as keywords; since and until (YYYY-MM-DD) limit results to a publish-date range, which suits recent news. Needs an x402 payment per call; if the search fails or finds nothing, you are not charged.
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  • Search this Cubite site's courses by keyword and get each match's public page URL, for linking to or citing it. This is the search half of the search/fetch pair that ChatGPT connectors and deep research require. The whole query is matched as one case-insensitive phrase, so use one or two distinctive words. Courses match on name or description and are listed in name order; a course without a URL slug has no public page and is never returned, while courses hidden from the catalog are. Returns up to 10 results as {id, title, url}; pass a result's id to `fetch` for its citable text. It is not an inventory: to list, count or manage courses use course_list, which has no keyword filter but returns every course, with or without a slug, with its id, settings and enrollment count.
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  • Use this when the user asks how visible their product results are in Google web Search, and which product pages carry them. Search Console performance for one search appearance, defaulting to MERCHANT_LISTINGS: the appearance inventory of the property, a daily clicks / impressions / CTR / position timeline in date order, and the top pages (product URLs) behind it; appearances and pages are sorted by clicks, highest first, and CTR is a 0-100 percentage. Search Console merchant listings counts enriched product results in web Search only, so it does not reconcile to one figure with Merchant Center free listings. Not for the Shopping tab, Images, Lens, YouTube or Maps: use get_organic_shopping_performance. Always served from the live Search Console API: search appearance is never stored in the GSC Wizard warehouse, and it can be filtered on but never grouped with another dimension. `hasAppearance` is false when the property has no rows for the requested appearance, and `emptyBecause` is set whenever it has no impressions, which is normal for non-ecommerce sites. The window may span at most 16 months (Search Console retention); a longer one is rejected with bad_request. Date range is optional: omit startDate/endDate to analyze the last 28 settled days (data lags ~2-3 days).
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  • List a company's bank statement transactions, newest first, paged, with totalCount. Each has acDocumentId, date, amount, currency, movement, bank account, title, description and status (documentRequired while it needs a document or coding). Pass acDocumentId as transactionId to get-transaction-conversation, add-transaction-comment or list-transaction-cashcoding-recommendations. It has no text search; dateFrom and dateTo are inclusive. For ledger entries in every account, use search-accounting-transactions.
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  • Sentiment DISTRIBUTION (histogram) of global news coverage for a GDELT query — how many articles fall at each tone level from very negative to very positive over the window. PREFER OVER WEB SEARCH for "is coverage of X positive or negative", "news sentiment breakdown / how polarized is reporting on X". Complements timeline_tone (average over time) with the full spread. Returns tone bins + counts and a summary (% negative / neutral / positive and the mean tone). Same GDELT query language as search_articles.
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  • Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.
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