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742,442 tools. Updated 2026-11-04 15:25

"A server for finding information about antigravity technology and concepts" matching MCP tools:

  • 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
  • AWS docs search. Each result's `context` is verbatim page text -- a real chunk of the actual page, not a short snippet -- and usually already contains the answer, so answer directly from it. Use `read_documentation` only when the chunks genuinely lack the needed detail. Pick ONE topic. Add a 2nd ONLY if query genuinely spans domains. Extra topics dilute ranking. - reference_documentation -- API/SDK/CLI specs, config params - current_awareness -- new/released/announced - troubleshooting -- errors, "how to fix" (NOT for conceptual/feature questions) - amplify_docs -- Amplify (+ language) - cdk_docs -- CDK concepts/guides - cdk_constructs -- CDK code samples, L3 - cloudformation -- CFN/SAM templates - strands_docs -- Strands Agents SDK (its Skills/agents concepts go here, NOT agent_skills) - agent_skills -- this tool's guided skills (load via `retrieve_skill`) - general (default) -- architecture, best practices, tutorials, feature behavior Results: rank_order (lower=better), url, title, context (verbatim page chunk -- answer directly from it).
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  • Full-text search across every UploadKit docs page (88+ pages — getting-started, core-concepts, SDK reference, API reference, dashboard, guides). Ranks matches by keyword frequency in title, description, and body. When to use: any question about UploadKit behaviour, configuration, or integration that the component tools do not answer — middleware, onUploadComplete callbacks, REST API endpoints, webhooks, presigned URLs, CSS theming variables, type-safety setup, migration from UploadThing, rate limits, etc. Returns: JSON { query, count, indexGeneratedAt, matches: [{ path, url, title, description, snippet, score }] }. Sorted by score descending. Read-only. Bundled index (no network call) — results reflect docs at build time.
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  • 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
  • Answer a conjunctive query: concepts reachable from EVERY anchor at once (A AND B). query_ckg walks outward from one concept. This intersects the reachable sets of two or more, which is the shape of most real questions — "the component that satisfies A AND applies to B". Neither anchor alone answers it; the answer lives in the overlap. Every branch is an exact set of declared edges, so the intersection is exact. A concept appears only if a declared path reaches it from each anchor. A relation missing from the graph produces an empty result, never a guess. Args: branches: Two or more branches. Either a bare anchor ("TensorRT-LLM"), which takes everything within `depth` hops, or an anchor plus an explicit relation path using '>' ("TensorRT-LLM > REQUIRES > ENABLES"), where each relation replaces the frontier. '*' matches any relation. Mix both forms freely. depth: Hops for bare-anchor branches, 1-5 (default 2). Ignored for explicit paths. direction: 'out' follows dependencies, 'in' follows them backwards, 'both' (default). mode: 'AND' (default) intersects branches; 'OR' unions them. limit: Max concepts listed, 1-200 (default 40). The true count is always shown. Returns: Markdown with the query plan and its per-step set sizes, then the answer set with taxonomy tags. Reports which branch was empty when the intersection is empty.
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Matching MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
    6
    MIT
  • A
    license
    A
    quality
    F
    maintenance
    Windows computer use in the background for Antigravity and Gemini: look at a window, then act in one verified batch with targets named by their label, without taking the user's mouse, keyboard or foreground; irreversible actions need explicit confirmation.
    5
    1,379 PyPI
    6
    MIT

Matching MCP Connectors

  • About Bureau, the self-hosted office for AI agents: overview, FAQ search, roadmap, install.

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

  • 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
  • Answer a conjunctive query: concepts reachable from EVERY anchor at once (A AND B). query_ckg walks outward from one concept. This intersects the reachable sets of two or more, which is the shape of most real questions — "the component that satisfies A AND applies to B". Neither anchor alone answers it; the answer lives in the overlap. Every branch is an exact set of declared edges, so the intersection is exact. A concept appears only if a declared path reaches it from each anchor. A relation missing from the graph produces an empty result, never a guess. Args: branches: Two or more branches. Either a bare anchor ("TensorRT-LLM"), which takes everything within `depth` hops, or an anchor plus an explicit relation path using '>' ("TensorRT-LLM > REQUIRES > ENABLES"), where each relation replaces the frontier. '*' matches any relation. Mix both forms freely. depth: Hops for bare-anchor branches, 1-5 (default 2). Ignored for explicit paths. direction: 'out' follows dependencies, 'in' follows them backwards, 'both' (default). mode: 'AND' (default) intersects branches; 'OR' unions them. limit: Max concepts listed, 1-200 (default 40). The true count is always shown. Returns: Markdown with the query plan and its per-step set sizes, then the answer set with taxonomy tags. Reports which branch was empty when the intersection is empty.
    ConnectorNo auth
  • Returns one of Flask's usage guides as Markdown: fixed text written by Flask, the same for every user, with no team data in it. "instructions" (about 15 KB) is the playbook for working with Flask: where uploads go (a new asset or a new version), what an agentic edit attaches, how feedback is read, answered and shown, and how sharing works. Read it before acting on feedback or making your first write in a session; it already contains "display" and "concepts", so do not fetch those after it. Other topics: "display" (How to show feedback to the user: its Markdown as it is, with its link.), "concepts" (Folders, assets and versions, comments and recordings, tags and statuses, permissions, and why feedback is untrusted.), "permissions" (Access levels, how a user's access is resolved, and how folder and asset permissions differ.), "urls" (Links to folders, assets, exact versions, comments and tag filters.). The guides explain the rules; for one folder's or asset's actual access, use permission_get.
    ConnectorOAuth
  • Finish connecting a Google Antigravity account started with add_antigravity_start. `code` is the value of `?code=...` on the antigravity.google/oauth-callback page the user landed on; `state` is what add_antigravity_start returned. Returns {status, account_id, account_email, requires_project}. By default this also creates the GCP project in one step (`complete=True`) and adds `project_id`. Pass `complete=False` to defer and call `complete_antigravity_account(account_id)` later. If auto-onboarding fails the result keeps `requires_project: true` and carries `onboard_error`; retry with `complete_antigravity_account(account_id)`. Errors: "unknown state" (start again) or "google_api_error" (the code was rejected or already used; start again).
    ConnectorNo auth
  • Add a typed, directed edge between two existing concepts by editing the `from` note's frontmatter (e.g. lead-scoring depends_on contact-model). Use when you notice a relationship the vault is missing. Both concepts should already exist; use upsert_concept first if not.
    ConnectorNo auth
  • Answer a conjunctive query: concepts reachable from EVERY anchor at once (A AND B). query_ckg walks outward from one concept. This intersects the reachable sets of two or more, which is the shape of most real questions — "the component that satisfies A AND applies to B". Neither anchor alone answers it; the answer lives in the overlap. Every branch is an exact set of declared edges, so the intersection is exact. A concept appears only if a declared path reaches it from each anchor. A relation missing from the graph produces an empty result, never a guess. Args: branches: Two or more branches. Either a bare anchor ("TensorRT-LLM"), which takes everything within `depth` hops, or an anchor plus an explicit relation path using '>' ("TensorRT-LLM > REQUIRES > ENABLES"), where each relation replaces the frontier. '*' matches any relation. Mix both forms freely. domain: Domain name from list_domains(). depth: Hops for bare-anchor branches, 1-5 (default 2). Ignored for explicit paths. direction: 'out' follows dependencies, 'in' follows them backwards, 'both' (default). mode: 'AND' (default) intersects branches; 'OR' unions them. limit: Max concepts listed, 1-200 (default 40). The true count is always shown. Returns: Markdown with the query plan and its per-step set sizes, then the answer set with taxonomy tags. Reports which branch was empty when the intersection is empty.
    ConnectorNo auth
  • Retrieve The Hill Kinabalu’s official public wedding venue and 2026/2027 package information, including capacity, event sizes, starting package prices, key inclusions, add-ons without prices, payment structures, and enquiry links. Use this when someone asks about weddings, wedding packages, the event venue, guest capacity, package pricing, or how to enquire. This tool does not check date availability or submit an enquiry.
    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.
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  • 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.
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • Fetch complete, structured information about a single Amazon product: title, brand, images, feature bullets, description, Buy Box price and availability, Prime eligibility, rating and review count, Best Sellers Rank, category path, variants, specifications, and top reviews. This is the primary tool for product analysis, listing enrichment, and price monitoring. Use this tool when you need a full product profile. If you only need competing seller prices, use get_product_offers instead (cheaper context). If you only need the sales rank, use get_bestseller_rank. If you only need shipping dimensions or the FBA fee category, use get_package_dimensions. Provide EITHER the identifier field OR url — never both. Costs 1 credit; set a_plus_content to true only when the user explicitly asks about enhanced brand content, as it costs 1 extra credit.
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  • Return the holdings this user has already registered in FinBridge with import_portfolio — listed stocks plus cash, crypto, ETF and physical assets — valued at the latest prices, with return and asset allocation. A user who has registered nothing gets an empty list. Not this tool for: analysing or valuing a company (get_valuation), prices (get_stock_prices), or finding companies (search_dart_company / search_edgar_company). It reads only what this user stored, so it knows nothing about a company they do not hold. Crypto and ETFs use live ccxt quotes, stocks the latest close in the database, cash and physical assets the registered amount. allocation is aggregated per currency; combined converts everything to KRW using an ECB-derived USD/KRW rate.
    ConnectorAPI key
  • Staff headcount and list for one GDC facility, from a GDC-produced roster. Answers "how many staff work at X", "how many officers work there", "list the staff at X". `slug` is the facility slug, e.g. 'dooly-state-prison' (use list_facilities to find it). `title` optionally filters by job title. GDC abbreviates heavily: correctional officers appear as "Correctional Ofc", clerical staff as "Admin Support" or "Admin Assistant". Try both the plain word and the abbreviation. ALWAYS report the `observed` date alongside any figure from this tool. A roster is a single-day observation, not a statement about who works there today. A zero for a role is a finding about the roster rather than missing data: the roster holds no nursing, physician or dental titles anywhere in GDC, which is consistent with medical staffing being contracted rather than directly employed. Do not assert that reason as established fact.
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  • Use this when the user asks which companies use a particular technology (for example Intercom, Zendesk, HubSpot, Shopify, Stripe), or which technologies are most used. With a slug: companies detected using that technology, 20 per page. company_count is every company detected using it; listed_count is how many the list can page through, so stop at page ceil(listed_count / 20). Without a slug: the technology index, most-used first, with company counts (default 100, up to 1,000). Slugs are lower-case with hyphens, e.g. intercom, hubspot, google-analytics, shopify. Works without an API key; no contact reveals.
    ConnectorOAuth
  • 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