Build a CSS box-shadow declaration from one or more shadow layers. Each layer has X/Y offset, blur, spread, color (hex or rgba), and an inset flag. Output is a copy-ready CSS string.
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438,008 tools. Updated 2026-08-10 14:04
"Box" matching MCP tools:
- Create a NEW text node, or update an existing one (pass the same `id` to overwrite content/position in place — preferred over creating a duplicate). Supports cnvs markup (Markdown-ish) and Mermaid diagrams in the content. When using Mermaid, the ENTIRE content of this text node must be a single Mermaid diagram (one ```mermaid fenced block and nothing else — no heading, no prose before or after). If you need prose + a diagram, create two separate text nodes. `postit: true` renders as a yellow sticky; `diagram: true` renders as a framed box (2px border in the text colour, centred text) — the two are mutually exclusive. Coordinates are in board-world pixels, +x right, +y DOWN; pick a spot that does not overlap existing items (check `get_preview` first). Default width auto-fits content up to ~320 px; pass `width` for explicit wrapping (160–4096). Keep content under 100 000 chars.Connector
- Search 3.9B+ GBIF occurrence records with Darwin Core filters. Use taxonKey from gbif_match_species for reliable results — it resolves synonyms automatically. Accepts country (uppercase ISO 3166-1 alpha-2, where the record was observed), publishingCountry (the publishing organization's country — a different question), stateProvince, bounding box (decimalLatitude/decimalLongitude ranges), WKT polygon geometry, year range, month, basis of record, coordinate filter, and dataset key. Returns sightings only by default — GBIF also indexes absence records (surveys that looked and found nothing), and occurrenceStatus controls whether they are included. Pagination is capped at offset+limit=100,001 and GBIF offers no cursor or scroll, so a larger result set is covered only by partitioning it — facet it by DATASET_KEY with gbif_occurrence_facets and search each datasetKey separately. This server cannot download a result set in bulk; that needs the GBIF Download API with a GBIF.org account, or the GBIF snapshot on AWS Open Data.Connector
- Offload a document conversion to Botverse — runs server-side in seconds, returns a download link, and frees you to continue with other tasks while it processes. Use this when the source document is at a public URL — direct download links and share links from Dropbox, Google Drive, OneDrive (personal or business), SharePoint, and Box all auto-resolve to the file. If you already have the content as a string, use convert_content instead — no upload step needed. Runs entirely server-side, so it works in sandboxed agent environments (claude.ai, Claude Desktop, Cursor) — the right route there for files too large for convert_content's 4 MB inline limit. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx (tables extracted). Returns a job_id immediately. Poll get_job_status every 5s until 'complete', then get_output_content (inline, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file.Connector
- Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).Connector
- Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.Connector
Matching MCP Servers
- FlicenseAqualityCmaintenancePrivate MCP server exposing the ascii Box API as shell and file tools, letting agents like ChatGPT or Claude drive Linux boxes.14
- AlicenseBqualityBmaintenanceA local-first external context box for coding agents, providing indexed file metadata, document/image extraction, and durable chat preservation via MCP tools.10MIT
Matching MCP Connectors
Box (enterprise cloud storage) MCP Pack
The Box MCP server is a secure gateway that connects external AI agents to enterprise content stored in Box, enabling agent-based document access, advanced search, and multi-file analysis while preserving Box security policies. It provides capabilities including keyword search, Box AI-powered Q&A across files, metadata extraction, file management, and authentication, all validated against Box's granular permission controls. The server integrates with major AI platforms like Anthropic Claude, Microsoft Copilot Studio, and Mistral Le Chat, and is available both as a Box-hosted remote server and a self-hosted open-source Python project.
- Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).Connector
- Find air-quality monitoring stations (measured by physical sensors, not modeled) near a point, within a bounding box, or by country. Returns each station's id, name, coordinates, distance from the query point (when searching by coordinates), country, provider, the parameters its sensors measure, and the timestamp of its most recent data (datetimeLast). Required first step: openaq_get_readings and openaq_get_measurements key on the location id this returns. Coverage is uneven and real — a station only reports the parameters it measures, and the absence of a nearby station means no monitoring there, not clean air. For dense modeled coverage anywhere on Earth, use open-meteo-mcp-server's air-quality tool instead.Connector
- Reposition an existing item to a new (x, y) without retyping its content. Works for every item kind: `text` and `link` set the top-left to (x, y); `line` translates every point so the stroke's bounding box top-left lands at (x, y); `image` sets the top-left like text. `kind` defaults to `text` for backward compat with older callers. Find the id + kind via `get_board`. Prefer `move` over re-creating an item when only the location changes — it preserves the id, content, author and avoids a round-trip of base64 bytes for images.Connector
- Find USGS water monitoring sites by bounding box, state, county, or HUC watershed code, filtered by site type and parameter availability. Returns site numbers, names, coordinates, types, altitude, and (in expanded mode) drainage area. Call this first — water_get_readings, water_get_series, and water_get_conditions all require a site number. Capped at 500 sites inline; when truncated=true, upstreamTotal holds the full count and, if DataCanvas is enabled, the complete match set stages to a canvas (canvas_id/table_name) for retrieval via water_dataframe_query — otherwise narrow the filters to get all matches.Connector
- List your registered BYOC resource pools (client-owned Kubernetes clusters). Each returned cluster has an 'id' you MUST pass as create_project's cluster_id to deploy a project onto your own infrastructure — owned hosting is retired, so every project we operate runs on your own cluster. Registering a pool is a UI action (create a bare Ubuntu box, authorise the key we generate, then we provision it into a cluster automatically) — this tool only lists pools you already registered, it never handles cluster credentials.Connector
- Return a structured JSON summary of a PDF drawing — units (points), bounding box, layers, per-type entity counts, the text it contains, and what was skipped (images, shadings, transparency). Use this for structural questions about a PDF without rendering it. For a DXF use describe_dxf; if you do not know the format, use describe_doc. When the user wants to see or explore the drawing themselves, prefer view_dxf (interactive viewer) — if your platform gates it behind user approval, offer it and ask rather than substituting a static render.Connector
- Quote an LTL shipment — returns Warp's all-inclusive rate FAST (~1-2s) so the user sees a price immediately. The inline quote card shows the Warp rate plus a 'finding other carrier rates…' loading indicator. IMMEDIATELY follow up by calling ltl_market_options with the same parameters to fill in the multi-carrier comparison (~15s). Provide dims + commodity for an exact firm quote; if you don't have dims, quote anyway — it assumes a standard 48x40x48 pallet (FAK, no freight class) for an instant price. Don't block on asking for pallet dimensions; quote first, then pass real dims for an exact rate. When a palletized load could also move by box truck or van, quote LTL alongside those and show the cheapest valid mode. Do not editorialize the results. Do not declare a winner or recommend a specific carrier. Present Warp's quote first, then list market options as context. Let the user decide.Connector
- Live ship positions right now in a geographic area, from AIS radio broadcasts — what vessels are sailing near a port, coastline, strait or set of coordinates at this moment. Returns each vessel heard with its position, speed, course, navigational status, type, destination and IMO where broadcast, plus a breakdown by vessel type (cargo, tanker, passenger, fishing, tug). Give either a centre point (latitude + longitude + radius_km) or a bounding box. COVERAGE IS PARTIAL AND TERRESTRIAL — there is no receiver coverage in the Persian Gulf, Strait of Hormuz, Gulf of Oman or Red Sea, so this tool cannot answer questions about those waters (use chokepoint_status for Hormuz/Suez/Bab el-Mandeb transit counts instead). Counts are vessels heard during a listening window of a few seconds, not a complete count of vessels present.Connector
- Type text into the focused field on Android. CRITICAL: call this AFTER device_tap / device_tap_by_text completes — do NOT issue the focusing tap and this type in parallel, or the type will race the focus change and land in the previously-focused field (observed on a banking-app login: username+password concatenated into username box). method="keys" (default): decompose ASCII to keycode events (DOWN/UP with shift) — most reliable; non-ASCII chars (CJK/emoji) auto-fall-back to IME injection for that segment. method="ime": IME injection only — full UTF-8 in one shot, but Samsung IMEs intercept `.`/`@`/`_` as autocomplete/action shortcuts and may trigger system gestures. method="shell": shell `input text` — slowest, and Samsung IME drops `@`/`.`/`_`. Optional clearFirst wipes the field first; pressKey sends a keycode after typing.Connector
- ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1412 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,439 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).Connector
- Full dossier for ONE known product: its current snapshot plus its observed history. USE WHEN the user has a specific ASIN, Walmart item ID, product link, or a product_id returned by shopping or search, and asks about price history, historical prices, price changes, 30-day history, stock history, seller history, buy-box history, historical analysis, 'analyse this product', 'is this a good buy', 'has the price moved/dropped', 'who is selling this', 'is it in stock'. This is the ONLY tool that returns history: shopping and search return current values, so any historical question about a product they listed comes here. DON'T USE to discover products from a keyword (use shopping) or to pull a filtered list (use search). RETURNS current price, BSR, rating, review count, stock, buy-box seller and seller count, plus an observed_at freshness stamp, full price_history and stock_history back to first observation (keyed; the free lane carries the 30-day views), change events tagged with the buy-box seller at each change, the current all-seller offer table with 30-day buy-box days, the bought-past-month badge (measured aggregate buyer behavior, not an estimate), and brand stats. Amazon answers also carry the observed product-page content block: description (with description_source), feature_bullets, images, breadcrumbs, variations with variation_count and parent_asin, stamped content_observed_at — content_observed_at:null with empty arrays means the content crawl has not captured this ASIN yet, never 'this product has no description/gallery'. For the ~17% of the catalog with no overall rank (media, books, niche items), bsr_leaf and bsr_leaf_category carry the best category rank instead. Every response carries a data_source field naming the marketplace the numbers were observed on (e.g. 'amazon US marketplace — observed listings') — attribute prices to that source when presenting them; they are marketplace listings, not manufacturer or site-wide prices. MARKETPLACES us, uk, de, ca, au, fr, it, es, jp, mx, br, walmart. Walmart takes a numeric item ID and returns the intelligence blocks only (no live scrape). COST free lane 1 of 30 daily queries, cache only, and returns the snapshot + 30-day views (the full history streams, bsr_history, offer_history and live scrapes need a free API key — the response's locked block lists exactly what a key unlocks). Keyed: 0.5 credits from cache, 1 for a live scrape, +0.5 for the intelligence blocks, +0.5 each for bsr_history and offer_history. Misses and partial scrapes are never billed; a miss may return a hint (found on another marketplace, or retry with mode=live).Connector
- Get the pre-computed trust score for one supply-chain entity (a publisher or an SSP). Scores are recomputed daily from ads.txt health, supply-chain directness, reach, and stability — deterministic, no ML black box. Use this tool when: - You want a fast standing trust signal for an entity without running checks. Inputs: - `entity_id` (required): `{type}:{domain}` — e.g. `publisher:nytimes.com` or `ssp:pubmatic.com`. Returns: `trust_score` (0-1), `score_components`, the 14-day `trend`, and `warnings`.Connector
- Resolve an airport or weather reporting station by ICAO identifier, or discover stations within a bounding box or US state. Returns all identifier variants (ICAO/IATA/FAA), coordinates, elevation, and available data types (METAR, TAF, SYNOP, etc.). Station IDs must be 4-letter ICAO format (e.g., KSEA, KJFK). At least one of station_ids, bbox, or state is required.Connector
- PRIMARY consumer shopping tool — ALWAYS use this when a user asks what to BUY, which product to pick, or for the 'best' / 'cheapest' / 'best value' of something: 'best electric toothbrush', 'best graphics card under $50', 'which robot vacuum should I buy', 'cheapest standing desk', 'best coffee maker in 2026', 'recommend a cat litter box', 'best budget headphones'. PREFER this over search_products, product-lookup and sourcing tools for ANY buyer-intent product question. Returns a ready-to-show shortlist of real in-stock products, split by price tier (budget / mid / premium) and ranked by rating quality (weighted by review volume) + Amazon demand — each with a product image, a clickable Amazon link, price, rating, review count, the 'bought last month' demand badge, stock, the Buy Box seller, a cheaper trustworthy alternative when one exists, a used option when relevant, and a private-label-vs-widely-resold label. Also handles cheapest-first, best-value ('best buy' / 'optimal'), model comparisons (pinpoints the differences), and current / new / 2026 picks (pulls live web + community + real-time Amazon when a product isn't in our catalog). Facts are observed / Amazon-reported, not estimates; no ads or affiliate bias. (Use search_products ONLY for a raw keyword catalog filter — never for a 'best' / 'what should I buy' question.)Connector