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786,062 tools. Updated 2026-11-15 20:36

"Search results for proofcut" 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 the live web with Keenable, a search engine built for AI agents. Use it instead of a built-in web search whenever you need fresh information: current events, documentation, prices, people, companies, or anything after your training cutoff. Answers in well under a second. Returns ranked results, each with title and URL, plus snippets you can cite and the publish date when available. Snippets usually answer the question; to read a page, use fetch_page_content. Example: {"query": "release notes for the latest Node.js LTS version", "published_after": "30d"} Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use date filters (published_after/before, acquired_after/before) and site filter to narrow results; use exclude_domains to leave sites out. Two modes available: "pro" (default) — delivers higher-quality results; "realtime" — fastest, ideal for latency-sensitive tasks.
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  • Surface cross-venue price discrepancies between Polymarket, Kalshi, and Limitless as a discovery feed for price discovery and divergence detection. Default threshold is 0.5% spread, below typical round-trip fees — most results are informational, not tradable arbitrage. Raise `min_spread` to 0.03+ for after-fee opportunities. The optional `query` parameter post-filters results by topic keywords on event titles — it does not perform a topic search; for topic-driven retrieval use `discover_markets` or `search_markets`. Pairs with missing volume data on at least one venue are flagged 'volume_unconfirmed'. All results are indicative only — not trade recommendations. Real-money venues only. Orderbook depth is not confirmed in Phase 1.
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  • Get retweets of specific post. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Database-only. Results include guidance for full mode. PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. Database-only search for historical retweet data. Date filter: OMIT startDate by default. ONLY pass if user explicitly requests filtering from specific date (YYYY-MM-DD format). IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. Use to analyze post amplification patterns. NOT for quotes - use getTwitterPostQuotes. Optional fields parameter for performance: ["id", "authorUsername", "createdAt"]. This is a safe, read-only tool for analyzing searchable information.
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  • Search hearings, floor sessions, and committee meetings. jurisdiction is required — the Open States events endpoint has no all-states search, so scope every call to a single state; use openstates_list_jurisdictions to pick one. Experimental — most states do not publish event data to Open States. Use after and before to scope to a date range. Set require_bills=true to filter to events with bills on the agenda, which is the most useful filter for tracking legislation through committee. Use include=agenda,participants for full meeting context. Empty results from an unfiltered search often indicate the state lacks event data rather than no events occurring.
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Matching MCP Servers

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    A local MCP server that gives Claude Code web search capabilities using DuckDuckGo, enabling discovery of URLs from natural language queries.
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    Enables plain-language web search with automatic source and time-window selection, returning relevance-ranked links and summaries to MCP clients such as Claude Code and Codex. Works as an MCP server, CLI, and Claude Code plugin with zero runtime dependencies.
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Matching MCP Connectors

  • Search Epinu real-asset projects. Returns bounded summaries only; call projects_get_deep_dive for detailed packets. Results include public projects plus the token owner's own archived, draft, or unpublished projects for duplicate checks; another owner's unpublished projects are never returned. Available without a token for public results only.
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  • Search companies that sponsor podcasts. All filters are optional and combine (AND). Results are paginated (default 25 per page, max 100); page depth is capped at 20 — refine the filters instead of paging deep. Each result carries the sponsor's domain, name, industry, location, sponsorship/podcast counts, and a representative buyer contact (masked on credit-based plans). Without a linked account, results cover only publicly listed sponsors with top-line stats (no contact or company-detail fields), the last 90 days, first page only, max 25 results. For one company's full profile use get_sponsor; for its buyer-contact list use list_sponsor_contacts.
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  • Re-run a previous patent search to get fresh results, repeating the inputs that steered it — the company scope, the hint, named products, markets, company sizes and the named standard. Free within 6 months of the original search, 1 search credit after that. Asks first either way: the initial call returns a quote listing the inputs it will repeat and whether it is free, and runs nothing until you call again with confirm: true. To narrow or re-read the results you already have, use claimhit_get_result instead — that is free and does not start a new search.
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  • Search published public fellowships, grants, scholarships, prizes, and funded residencies. For matching, start with separate broad calls for the exact topic, synonyms, broader fields, and type-only grants and fellowships. Do not stack sparse topic, career, and location filters during initial discovery. Array values are OR alternatives within one filter; separate filter fields are combined with AND. Search results are candidates only: call get_opportunity before ranking or citing each one.
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  • Search a registry for packages matching q. registry=all fans out to npm, Docker Hub, and the VS Code Marketplace and merges the results. PyPI has no public search API, so registry=pypi returns 400 not_supported — look a PyPI package up by name via get_package instead. Results are normalized PackageSummary items (npm adds a relevance score; Docker adds isOfficial).
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  • Resolve a city or airport name or code before searching flights. Returns typed values such as city:SHA to search every catalog airport in Shanghai or airport:SHA for Hongqiao only. Pass the selected value unchanged to search_flights. Ask the traveler when multiple results are plausible.
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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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  • 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 job listings on Jobily.gr, the Greek job board. Filter by free-text term, role/location/sector slugs, company, employment type, workplace type and work time. Use lookup_roles_and_companies, lookup_locations and list_sectors to discover valid slugs — unrecognized slug filters are reported in matchedCriteria.unrecognizedTerms and ignored by the search. Returns up to 20 jobs per page with the total count, facet counts (first page) and recovery suggestions when nothing matches. Search results do not include job descriptions — call get_job with a result's guid for the full posting. When total is large (100+) and few filters are active, recommend the user narrow their search using the facets or lookup tools rather than paginating through hundreds of results.
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  • Fetch a LIVE Amazon search-results page (SERP) right now — the ranked organic + sponsored listings a shopper would see this minute for a query, with position, ASIN, title, price, rating and badges. Use when the user wants CURRENT ranking/visibility: 'who ranks for "dog bed" on Amazon right now', 'is my ASIN on page 1 for this keyword', 'what's sponsored vs organic for this search'. This is a real-time fetch (takes ~10-40 seconds) — for warehouse keyword search use search_products; for buying advice use shopping_search. Amazon marketplaces only; up to 3 pages per call.
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  • Search memories by keyword. The query must use vocabulary that appears in stored labels, descriptions, or tags — not intent summaries or paraphrases. Pass node_kind (space-separated) to list or search within specific kinds — unrelated kinds that happen to match query text are excluded. Omit query with node_kind set to list matching kinds ordered by most-recently-updated. Default limit: 10. Use exact=true for identifiers (ticket numbers, short codes with hyphens) — FTS tokenises hyphens away so 'PROJ-042' is not found by default. If search returns zero or truncated results, use orient (with domain) to browse all memories, then recall by ID, then follow connections from a known memory. Returns lean results only — id, label, and a truncated why_matters excerpt; call recall(id) for full content. When a list or section has 2 or more results, each is rendered as a single compact text line — "[id] label — excerpt (domain, node_kind)" — instead of a JSON object; exactly one result is returned as a full object. exact=true is exempt — it always returns full objects, regardless of result count. state (space-separated union) post-filters results to memories with any of the given lifecycle states: none | resolved | superseded | contested. Response always includes semantic_attempted (bool: true when embed() succeeded and the vector path was entered) and semantic_best_dist (float|null: cosine distance of the top result after filtering, null when no vector rows were returned). Use these to diagnose whether Bedrock was available and how close the best match was. On failure, content[0].text is JSON: {"error_class": "retryable|forbidden|internal", "message": "..."}. Switch on error_class: retry on retryable.
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  • WHEN: object name is unknown, partial, or you need to find by concept/keyword. Search the D365 F&O knowledge base for X++ code, tables, classes, forms, views, enums, EDTs, security objects using natural language or partial names. Returns ALL chunks (metadata, Declaration, methods) for the top-scoring objects so the LLM has complete context on the first call. Lower-scoring results return a short preview. No follow-up get_object_details call is needed for top results. NOT for listing all objects in a model -- use list_objects for that. NOT when the exact name is known -- use get_object_details for that. NEVER call search_d365_code twice in the same conversation turn. If one search did not find the object, answer from what you have -- do not repeat the search. When you need context on MORE THAN ONE concept simultaneously, use batch_search instead -- it runs all queries in parallel and is faster. NEVER call for ADO items (FDD, RDD, IDD, Bug, Task, PR, WorkItem, sprint, #1234) -- use ado_* tools instead.
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  • Search the Extend documentation. Returns matching pages with URLs — results are pointers, not content: fetch the most relevant with get_documentation. An empty results list means nothing matched; different domain terms (feature names, API field names, product vocabulary) usually do. Always available, no workspace targeting.
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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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  • The top organic results and SERP features Google shows for one query. Use when: "what ranks for X", "who is on page one for X", "is there a featured snippet or AI overview for X". Not for: where one site ranks for a keyword, use seo_get_position (it scans the top 100 for you). Keyword ideas, use seo_search_keywords. The businesses Google Maps ranks for a local search, use maps_search_places. Returns: Record. features[] (featured_snippet, people_also_ask, video, ai_overview and others), results[] (rank, organic_rank, type, url, domain, title, snippet, published_at, rating), related_searches[], ai_overview (text, references[]) or null, results_count, check_url. depth counts organic rows: the default returns 10 organic results whenever Google has them, with the features ranked among them on top. Each People Also Ask question and each forum thread is its own row at its block's rank; for a question, title is the question and snippet the answer, url null when Google's answer is an AI overview. domain is null on a row whose url is still a google.com/goto redirect. location localises the local pack, not the organic rows of a bare service search: put the town in the keyword ("dentist columbus ohio") for local organic results. Paid ads seldom come back, so the page says nothing about who bids on the query; a named rival's search ads are in ads_get_advertiser_ads with platform google. Cost: 1 credit per 10 results, +1 with ai_overview. Default top 10 = 1 credit. Cached 24 hours. Example: {"keyword": "hubspot alternative", "depth": 10, "ai_overview": true}
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