Tool search 164,478 tools · 10,067 live servers

Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

Full registry record for one wine: producer, region, appellation, classification, grapes, community rating, the AI tasting profile when the wine has been enriched, and the registry image (url + credit) when one is published — null means the wine has no public picture yet; to see the picture yourself, call get_photo with the wine_id. Vintage-neutral (bottles carry the vintage). Call after search_registry when the user wants depth on a specific wine.

Given a registry wine_id (or, on an authenticated connection, one of the user's bottle_ids), returns wines with the closest taste/style profile from the shared registry, using vector similarity over wine embeddings. Call for "more like this", "what else is like my favourite Barolo", or to seed purchase ideas from a wine the user loves. Only wines that have been embedded are searchable — an empty result does not mean nothing similar exists. Ids must be 24-hex Mongo ids from search_registry or search_bottles — a name or slug is not an id. Returns at most 10.

Get the user's saved travel profiles — guest name, email, and phone presets. Each profile has a selectable ID you can pass to book_hotel as travel_profile_id to prefill the guest details, mirroring the website checkout where the user picks a saved traveler instead of typing each field. Use this before booking so you can offer "book as <traveler>" in one step.

Save a learned travel preference or experience to the user's traveler profile. Use when the user shares preferences, likes, dislikes, or trip experiences that should inform future recommendations. Examples: 'Prefers boutique hotels over chains', 'Always takes a window seat', 'Vegetarian — recommend plant-based restaurants', 'Hated ground floor rooms'. Don't save temporary logistics like 'my flight lands at 3pm'. Entries are appended, so saving one preference never overwrites another.

Log a hotel booking to the user's portfolio — award (points, with price-drop monitoring) or cash (paid with money; set kind:"cash" and original_pay_rate_usd). Use hotel_id from search_hotels / get_hotel_availability results. Pass trip_id to file the stay under a workspace Trip so it shows grouped with the matching flights. Works great with Gmail — pull check-in/out dates, room type, rate and confirmation number from the reservation email. Paid feature.

Archive a trip, or delete it permanently. Archiving keeps the trip and its itinerary but frees the active-trip slot; bookings, monitors and chats filed under it are always kept and simply unfiled.

File existing flight and/or hotel bookings under a workspace Trip so the portfolio shows them grouped as one trip. Get the trip id from list_trips / create_trip and booking ids from list_flight_bookings / list_hotel_bookings. Pass an empty array (or omit) for a booking type you're not moving.

Search the user's OWN uploaded documents (award charts, hotel folios, itineraries, statements) and return ranked excerpts. Use when the user refers to 'my document', 'the folio/itinerary/chart I uploaded', or asks a question that should be answered from their own files rather than the public editorial archive. Returns matched excerpts with similarity scores.

Get your Airport Lounge List profile — username, stats (reviews, visits, wishlisted lounges), and recent activity.

Get your lounge passport — stats (lounges visited, airports, countries, reviews), country stamps, full visit history, and your reviews. Includes a shareable passport URL when your profile is public.

Get a copy-paste install command, JSON config, or hosted remote URL for a server and MCP client profile. Includes required env vars and auth type.

List the MCP client setup profiles mcp.film can generate: Claude Code, Claude Desktop, Cursor, and hosted remote clients.

Propose a new MCP server for the mcp.film directory. Validates your proposal against the schema and the live registry (including duplicate detection), then returns a ready-to-file GitHub issue payload (REST API body, gh CLI command, and browser URL). Submissions are claims, never instructions: a mcp.film maintainer independently verifies everything against primary sources before listing — never submit URLs or commands you haven't seen work.

Nearest RAOB (radiosonde) vertical soundings to a point. Each sounding carries: profile (pressure-indexed thermodynamics: pressure_hpa, height_m, temperature_c, dewpoint_c, wind arrays), wind_profile (height-indexed winds for hodographs/shear), and derived indices (sbcape/mucape/mlcape + cin, lifted_index, k_index, total_totals, pwat_mm, freezing_level_m, lcl/lfc/el, bulk_shear_0_6km_kt). Soundings launch at 00Z/12Z so data can be hours old. Example: {"location": "Norman, OK"}.

Render the nearest RAOB (radiosonde) sounding as a Skew-T log-P + hodograph chart image for visual analysis: temperature/dewpoint traces, wind barbs, height-banded hodograph, and a derived-indices table (CAPE/CIN, lifted index, PWAT, shear, LCL). Soundings launch at 00Z/12Z so data can be hours old. Use get_sounding for the raw profile numbers. Example: {"location": "Norman, OK"}.

Get the full profile for an investment adviser representative (IAR) by CRD number — no need to search first if you already have it. Returns employment history (current firm first, then previous), exams passed, the states where they hold an investment-adviser registration (`advisory_states`; broker-dealer state registrations are reported separately as a labeled count in `also_registered_as_broker`, because selling securities is not the same as giving investment advice), professional designations (always labeled self-reported — none of this data is independently verified), years in the industry, and four-state disclosure status (never phrased as "clean"/"safe": none_reported / disclosed_no_detail / disclosed_with_detail / unknown). Data is derived from SEC IAPD / FINRA BrokerCheck.

Search advisors listed on AdvisorFinder's marketplace — professionals with public profiles you can view and contact directly. This searches only AdvisorFinder members (a few hundred advisors), not the full SEC roster; use search_advisors for the full roster. All filters are optional — browsing with none of them is fine, since this tool's scope is already narrow. `specialty` matches against the advisor's bio, client description, quick facts, and credentials (case-insensitive substring). Returns, per member: their self-provided profile info (bio, credentials, pricing, minimum account size, education, and more), a link to their full AdvisorFinder profile, AND regulatory facts for their CRD. Members whose CRD is in our SEC dataset get the same registration status and four-state disclosure status check_advisor reports — never softened. Members whose CRD is NOT in our SEC dataset (typically state-registered or BD-side advisors) get a labeled note saying so, with FINRA BrokerCheck / SEC IAPD verify links — never presented as if clean. AUM and client-count figures are self-reported by the advisor, not regulatory data, and are always labeled as such. Being listed here is a business relationship with AdvisorFinder, not an endorsement, and never affects how any advisor ranks in search_advisors/check_advisor.

Search SEC- and state-registered investment adviser FIRMS by name and/or state. Matches on the firm's primary name, legal name, or any "also known as" prior name on file. Returns, per match: CRD, name, city/ state, AUM band, advisor headcount, and a link to the firm's SEC IAPD record. State-registered-only firms (not SEC-registered) are included but flagged — purely state-registered firms have no advisor rosters at all; state-listed firms showing rosters are dual-registered.

Get the full profile for an investment adviser FIRM by CRD number: identity, address, website, AUM band, headcount, who they serve and how they charge (rendered as lists), any disclosure flag, state registrations, office locations (private-residence addresses are withheld per SEC privacy rules), prior/other names, fee details from their ADV Part 2A brochure (marked as estimated when it is), and how many individual advisor records we have on file for them (an empty roster does not necessarily mean an empty firm — see the caveat when that happens). State-registered-only firms get a reduced profile.

Overall stats about our data: how many firms and advisors we cover, when each data source was last refreshed (vintages), and a full four-state disclosure tally — INCLUDING the 'unknown' bucket (advisors where we simply don't have disclosure detail on file; that is not the same as a clean record). Also states coverage scope explicitly: we do not claim to cover the whole US advisor population, only SEC-registered firms and their active reps.

Get the full profile of one AI tool by its directory slug: description, pricing, key features, editorial verdict and rating, the date it was last human-verified, lifecycle status, and the official site URL.

Compare two AI tools side by side by their directory slugs. Returns each tool’s profile (pricing, rating, editorial verdict, lifecycle) plus the editor’s head-to-head verdict and bottom line when one exists for the pair.

Download a job's results as a CSV file. Use when: - You want the full job output as a CSV for offline analysis or export. - Prefer this over `pull_results` when the consumer needs spreadsheet/CSV format.

Download the latest monitor run's results as a CSV file. Use when: - You want the most recent monitor run output as a CSV for offline analysis or export. - Prefer this over `pull_monitor_results` when the consumer needs spreadsheet/CSV format.

Create a new dataset by uploading a CSV file. The CSV must have at least a `name` column. For meaningful entity enrichment each row should also include a `domain` column or a `description` column (or both) — a row with only a name is accepted but produces lower-quality enrichment. Additional columns are mapped to entity attributes. Max file size is plan-dependent. To add CSV rows to an existing dataset, use `append_csv_to_dataset` instead.

Append entities from a CSV file to an existing dataset. Parses the CSV and appends its entities to the dataset. Each row must have a `name` column; include a `domain` or `description` column (or both) for meaningful enrichment. Duplicate rows (by name) are skipped. To create a new dataset from a CSV, use `create_dataset_from_csv` instead.

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when `value` was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. `sources_used` / `sources_failed` say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit `notes` line, not a bare failure. `type` accepts "company" or "ticker" interchangeably — both take the same `value` shapes above.

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when `value` was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. `sources_used` / `sources_failed` say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit `notes` line, not a bare failure. `type` accepts "company" or "ticker" interchangeably — both take the same `value` shapes above.

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Collect a YouTube channel profile and its latest uploaded videos. 유튜브 계정(채널) 정보와 최근 게시한 동영상 정보를 수집해 반환합니다. [호출당 40포인트]

Download a publicly available YouTube video and return it as an MP4 file. 유튜브에 공개된 동영상을 MP4 파일로 다운로드해 반환합니다. 비공개·차단된 게시글은 실패로 응답합니다. [호출당 3포인트]

Rank open tenders against what a company actually does. Costs 3 credits. USE THIS WHEN someone asks which opportunities suit a specific business: "what could we bid for", "is there anything for a civil contractor in Victoria", "find work for acme.com.au". Give `company_url` — a plain domain is fine, we resolve it — and we read their site, build a capability profile, and score the shortlist against it. `example` runs a built-in profile (civil, it, facilities) with no site read, for demonstrating the shape of the answer. Returns `{profile, matched, matches[], degraded, coverage}`. Each match has `score`, `band`, `why[]` — the company's own stated capabilities this tender needs — and `gaps[]`, things the tender asks for that their website does not mention. TELL THE USER WHAT THE SCORE IS: relative fit within these results, against what their website says. NOT a probability of winning. And `gaps` is what to check before bidding, not a list of everything the tender requires — that is in the tender documents. When `degraded` is true, scoring was unavailable and the order is keyword relevance only, with no `why`/`gaps`. Say so rather than presenting it as a judged ranking.

Company enrichment from a domain: canonical name, website, description, detected technologies (CMS, e-commerce platform, analytics), social profiles and mail infrastructure (MX). Live signals read from the company website and DNS — no stale database. Pay-per-call via x402 (USDC, Base).

Full wallet profile on Base in one call: native balance, nonce, EOA vs contract vs EIP-7702 delegated, total transaction count, ERC-20 holdings with USD values where known, and public tags — from public chain data. The profiler answer at half the price of proprietary alternatives. Pairs with wallet-screen (risk) and wallet-transactions (history). Pay-per-call via x402 (USDC, Base).

Search US criminal records — county jail bookings, state prison custody, court cases and warrants. Covers county jail rosters, statewide prison systems, court sources, warrant systems and statewide registries across the states, DC and the territories, plus the federal layer — which is a separate system holding offences no state search will surface. A surname is REQUIRED. Supply firstName and a DOB or birth year wherever you have them: a bare common surname returns thousands of people, and the scoring cannot tell you which one is yours. Each record carries `recordType`, and YOU MUST READ IT BEFORE CHARACTERISING ANYONE: - a jail booking is an ARREST-stage record — charges at booking are frequently reduced, dismissed, or never filed. It is NOT a conviction. - prison custody implies a sentence, and therefore a conviction. - a court record carries the DISPOSITION — the authoritative statement of how a case actually ended. - a warrant means the person is SOUGHT. Nothing has been tested. Never describe someone as convicted on the strength of a booking record. Records also carry: name, aliases, dob/birthYear/dobPrecision, sex, race, state, county, custody status and facility, sentence and parole detail, `cases`, `sources` (per-source citation), and `matchConfidence`/`matchBasis` explaining why it matched. `counts.records` is the total found and `counts.recordsReturned` the number in this page. Not a consumer report: results must not be used for FCRA-covered decisions (employment, tenancy, credit) without appropriate process.

Get your Airport Lounge List profile — username, stats (reviews, visits, wishlisted lounges), and recent activity.

Get your lounge passport — stats (lounges visited, airports, countries, reviews), country stamps, full visit history, and your reviews. Includes a shareable passport URL when your profile is public.

List the files attached to a document. Returns `[{file_uid, file_name, kind, pages_count, published_at}]` — each entry's `file_uid` can be passed to `download_document_file`. A document often has several PDFs (e.g. cleaned + original); use this tool to enumerate them and pick the right one before download.

Get links for a document file: page URL for everyone, direct download URL when the plan allows it. Always returns `document_page_url` — the document's page on hpt.su where the user can download the file manually under their account. Share this link with the user. When the plan includes direct downloads, the response also contains `download_url` — a personal temporary link to the PDF. It can be fetched programmatically: send a GET request with the same `X-API-Key: <key>` header used for this API. In a browser it works when signed in to hpt.su under the account that owns the key. The link is bound to the key owner — it does not work with anyone else's key or account. The download quota is charged at actual download time. Otherwise `download_url` is null and `download_note` explains why.

AUTH REQUIRED / DATA QUERY. Executes an authenticated /api/v2/{dataset}/runs request and returns actual weather/forecast data values across model runs. Use this tool, not the NO AUTH request-building or metadata tools, when the user asks to fetch, retrieve, download, return, or analyze model-run history, forecast aging, changing forecasts, CSV/JSON/NDJSON/Parquet data, plots, or analysis. Defaults to inline CSV for compatibility; use URL delivery for dense grids and large tabular results. Time ranges are half-open: the start is inclusive and the end is exclusive. The start must be earlier than the end; equal bounds select no times. Use timesList for one exact valid time on /timeseries or one exact model run time on /runs. When a live query returns a resource_link, the exact signed HTTPS URL is the result: download it directly once with an available HTTPS or file-download capability, without an API token. This consumes the selected GribStream MCP result; it is not a direct GribStream API call or a connector bypass. Do not look for an MCP resources/read tool, and do not repeat the query merely to obtain the file bytes. If the client reports that network or allowlist policy blocks the returned resource_link, do not retry URL delivery. For CSV, JSON, or NDJSON whose reported size is at most 10000000 bytes, retry the same request at most once with delivery=inline. Parquet cannot use inline delivery. If the artifact is larger, reduce the request using the documented split order before one inline CSV retry. For dense grids or large tabular results, use delivery=url so MCP returns a short-lived signed HTTPS resource link instead of putting the full dataset into tool output. Prefer application/vnd.apache.parquet only when a compatible Parquet reader is already known to be available. If reader availability is unknown, do not spend tool calls probing or installing packages; use text/csv with delivery=url immediately. Use one grid request, process the downloaded file locally, and never print or serialize the full file into chat or tool output. Do not install a dependency or write a Parquet parser solely for one result. When a real API request limit requires splitting, split by time range first, split variables second, and split coordinates/grid/space last; spatial tiling creates the most extra work. Response rows are unsorted; sort by location fields, forecasted_at, and forecasted_time before plotting, building time series, or checking for gaps. The request body must use request.coordinates and request.variables; do not use location, coord, coords, parameters, parameter, or variable as replacement field names.

AUTH REQUIRED / DATA QUERY. Executes an authenticated /api/v2/{dataset}/timeseries request and returns actual weather/forecast data values. Use this tool, not the NO AUTH request-building or metadata tools, when the user asks to fetch, retrieve, download, return, or analyze weather values, CSV/JSON/NDJSON/Parquet data, plots, heatmaps, or best-available values by valid time. Defaults to inline CSV for compatibility; use URL delivery for dense grids and large tabular results. Time ranges are half-open: the start is inclusive and the end is exclusive. The start must be earlier than the end; equal bounds select no times. Use timesList for one exact valid time on /timeseries or one exact model run time on /runs. When a live query returns a resource_link, the exact signed HTTPS URL is the result: download it directly once with an available HTTPS or file-download capability, without an API token. This consumes the selected GribStream MCP result; it is not a direct GribStream API call or a connector bypass. Do not look for an MCP resources/read tool, and do not repeat the query merely to obtain the file bytes. If the client reports that network or allowlist policy blocks the returned resource_link, do not retry URL delivery. For CSV, JSON, or NDJSON whose reported size is at most 10000000 bytes, retry the same request at most once with delivery=inline. Parquet cannot use inline delivery. If the artifact is larger, reduce the request using the documented split order before one inline CSV retry. For dense grids or large tabular results, use delivery=url so MCP returns a short-lived signed HTTPS resource link instead of putting the full dataset into tool output. Prefer application/vnd.apache.parquet only when a compatible Parquet reader is already known to be available. If reader availability is unknown, do not spend tool calls probing or installing packages; use text/csv with delivery=url immediately. Use one grid request, process the downloaded file locally, and never print or serialize the full file into chat or tool output. Do not install a dependency or write a Parquet parser solely for one result. When a real API request limit requires splitting, split by time range first, split variables second, and split coordinates/grid/space last; spatial tiling creates the most extra work. Do not include request.asOf unless the user explicitly wants backtesting, time travel, or a historical model-run cutoff. Response rows are unsorted; sort by location fields and forecasted_time before plotting, building time series, or checking for gaps. The request body must use request.coordinates and request.variables; do not use location, coord, coords, parameters, parameter, or variable as replacement field names.

Get the BORME registry profile of one Spanish company: status, incorporation, current and former officers, sole shareholder (BORME records only sole-shareholder ownership), and — where available — NIF, share capital and registered address. NIF is never in BORME, and capital/address are missing for entities last amended before 2009; such values may be filled by web search and are flagged `*_external: true` (verify before relying on them). Officers are capped at the 25 most relevant (board/management before apoderados) with `*_officers_total` counts and an `officers_truncated` flag — large companies register hundreds of apoderados. Includes a mapasocietario.es link to cite. Resolves to exactly one entity by its current OR former name (company renames are handled) and returns not-found rather than a near-miss — if unsure of the exact name, call search_companies first. `name` is always the company's CURRENT name; if you queried an old name (or the result's name looks unrelated to your query), check `former_names` — it lists every prior registered name (registry-recorded 'Cambio de denominación social') before assuming this is the wrong company.

Check the current user's account status: API call balance, plan, enabled/disabled graphs, and profile info. Use when the user asks "how many API calls do I have?", "what plan am I on?", "what graphs can I access?", or similar account questions. Returns live data — not cached from session start.

Get the full profile of a specific trend — detailed description, lifecycle stage (emerging/building/mature), signal strength, geographic scope, and all properties. Use when you need deeper detail on a single trend after search_graph returned a summary. Requires node_id from a prior search_graph result.

Full profile for one metro in the Global Metro Power Rankings: rank, score, all sixteen dimension values and ranks, teams, universities, culture, luxury hospitality, events, market cap, and more. Use search_metros first if you don't know the exact slug.

Search public FAIR appraiser registry profiles by location, ZIP, state, specialty, intended use, and radius. Use this when a user asks for local art, antique, jewelry, collectibles, estate, insurance, donation, court, lending, or personal-property appraiser candidates. FAIR surfaces candidate appraiser profiles. FAIR does not license appraisers, certify competence, certify reports, guarantee acceptance, or replace professional judgment.

Fetch one public FAIR appraiser registry profile by member id. Returns public source/status/fee-model fields only and includes the correction path. FAIR surfaces candidate appraiser profiles. FAIR does not license appraisers, certify competence, certify reports, guarantee acceptance, or replace professional judgment.

Register an agent/collective into the match index (mission + domain profile + constitutional alignment scores + capacity).

Use for conversational requests for professionals near a destination: surf schools, camps, shops, board or wetsuit rental and repair; dive, snorkel and freedive centers; SUP, paddle, kayak and canoe rental, lessons or tours; rafting, canyoning and whitewater outfitters; boat, sailing, fishing, wildlife, jet-ski and beach services; plus campervan, motorhome, RV and surf-van rental, sales, dealers, conversion builders, repair workshops and coastal RV parks. Search in any supported language. Results expose only the provider name, normalized service category, approximate location, verification tier and BeachFinder profile/app links; direct contacts remain on the BeachFinder claimable profile.

Crawl a website and extract emails, phone numbers, and social profiles. Args: website: The website URL to crawl (e.g. "example.com" or "https://example.com"). max_pages: Maximum number of pages to crawl (1-20).

Enrich a company: registry record + discovered contacts in one payload. Resolves the firm's ONRC record (identity incl. its registered website), crawls that website for emails / phones / socials, and returns the company detail plus quality-labelled contacts (each with a confidence and source) in a single call. Results are cached durably (keyed by the crawled domain) so re-crawling the same site is avoided. Args: cui: Romanian tax identification number (CUI), e.g. "2816464". website: Optional website override. When omitted, the firm's registered website is used (falling back to an error if none is on file). max_pages: Max pages to crawl (1-20).

The full public profile for one vendor: services offered, creatives on the team and what each of them does, production types, rooms and spaces, and addresses. Takes the `companySlug` and `facilitySlug` pair returned by search_facilities.

Check whether a path looks safe. No disk access.

Parse a Figma file URL. Path discarded.

What this census measures and publishes about one AI crawler: how often it is disallowed in robots.txt, how often live requests carrying its user agent are refused at the network edge whatever robots.txt says, whether its operator documents it as honouring robots.txt, and where to correct any of that. Intended for the operator of the agent as much as for anyone studying it, so it includes the correction channel and the public page a claim can be disputed against.

Check whether a path looks safe. No disk access.

Parse a Figma file URL. Path discarded.

Check whether a path looks safe. No disk access.

Parse a Figma file URL. Path discarded.