Tool search 103,805 tools · 5,318 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, and the AI tasting profile when the wine has been enriched. 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 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.

Get comprehensive data for a stock, ETF, or crypto ticker. Returns: - ticker, name, type (e.g. 'stock', 'etf', 'crypto'), industry - latest_price, page_url - bullish_case, bearish_case, potential_outcomes, takeaway, analysis_date (AI-generated) - price_forecast_days, price_forecast_percent, price_forecast_lower/upper_bound_percent (model price forecast) - future_uncertainty_urls: dict with image URLs for future_uncertainty, term_structure, volatility_surface, return_profile (when available) - future_uncertainty_last_updated, term_structure_last_updated - iv_rank_percentile (0-100, IV rank over past year) - long_vol_call, long_vol_put, short_vol_call, short_vol_put: full option pack dicts (when available) Throws an error if the ticker is not recognized. Args: ticker: Ticker symbol, e.g. 'AAPL', 'AMZN', 'BTC', 'ETH', 'SPY'.

Get comprehensive bias analysis for a news source. Returns: - source_name, slug_name, page_url - source_match: original query and deterministic match method - articles_analyzed: total articles in the bias database for this source - last_updated: source-profile aggregation timestamp - avg_social_shares: average social shares per article - emotionality_score (0-10): how emotional the writing is - prescriptiveness_score (0-10): how much the source tells readers what to think/do - bias_values: canonical plain-text source-level weighted display scores (-50 to +50 bipolar, 0 to +50 unipolar). Keys match the article tools; these are directional source summaries, not raw article-score averages. - bias_scores: legacy emoji-prefixed display scores - bias_score_methodology: scope and evidence caveats for aggregate scores - bias_description: clean-text, AI-generated overall bias summary narrative - bias_description_metadata: generation time, automated review status, and evidence scope - bias_description_html: optional website HTML when include_html=true - liberal_conservative_description: narrative on political leaning - libertarian_authoritarian_description: narrative on authority stance - signature_phrases: words/phrases uniquely overrepresented vs other sources - signature_negative_phrases: uniquely negative/alarming phrases - most_shared_phrases: phrases in their most viral articles - most_emotional_phrases: phrases used in their most emotional articles - pays_for_traffic_keywords: keywords this source buys ads for - similar_sources: sources with the most similar bias profile - most_different_sources: sources with the most different bias profile - trends_graph_url: URL to a chart of this source's coverage volume over time - bias_plot_urls: dict of 2D bias scatter plot image URLs (political_lib_auth, subjective_objective, informative_opinion, oversimplification_factful) — only present when available - recent_articles: list of most recent articles with full article fields, bias_values, analysis status, and optional self-contained bias_dimensions and bias_analysis. Evidence quotes include verification method and exact character offsets when available. - recent_evidence_coverage: reconciled counts for verified, unverified, partial, legacy-scored, and pending articles, plus evidence-bearing count and verified ratio Throws an error if the source is not found. Args: source: Source name, slug, or domain (e.g. 'Fox', 'reuters', 'bbc.co.uk'). Partial names are accepted only when they identify one source; ambiguous input returns candidates. recent_articles: Number of recent articles to include (1-50, default 10). include_evidence: Include per-article claims, verbatim evidence, counterevidence, confidence, rationale, and limitations. Defaults to false to keep multi-article source payloads compact. include_html: Also return the original website-formatted source narrative. Defaults to false.

Book a hotel room using a rate from get_hotel_details. Requires a Gondola account (API key) and a saved payment method. Use get_payment_methods to find your payment ID. The gondola_rate_id comes from the room rates returned by get_hotel_details — each room option has a rate ID you can use here. Guest details (given_name, family_name, email_address, phone_number) can either be passed directly or prefilled from a saved travel profile: pass travel_profile_id (from get_travel_profiles) to book "as <traveler>" without collecting each field. Any field you also pass explicitly overrides the profile. To earn points and elite credit, pass loyalty_account_id — use the Member Number from get_loyalty_accounts that matches the hotel's chain (e.g. the World of Hyatt account for a Hyatt property). When a loyalty_account_id is passed, the booking goes out under the email registered to that membership (overriding any travel profile or email_address), so the stay credits to the right account. Args: gondola_rate_id: The rate ID from get_hotel_details room rates. payment_id: Payment method ID from get_payment_methods. given_name: Guest's first name (optional if travel_profile_id is provided). family_name: Guest's last name (optional if travel_profile_id is provided). email_address: Guest's email for confirmation (optional if travel_profile_id is provided). phone_number: Guest's phone number with country code (optional if travel_profile_id is provided). special_request: Optional special request for the hotel (e.g. "high floor", "late check-in"). loyalty_account_id: Optional Member Number (from get_loyalty_accounts) to earn points. travel_profile_id: Optional travel profile ID (from get_travel_profiles) to prefill guest details. Returns: Booking confirmation with ID and details, or an error message.

Analyze the user's whole loyalty portfolio and surface the highest-value actions. Trip-independent. Looks across every loyalty program the user holds — plus the transferable card currencies (Amex, Chase, Bilt, etc.) that can feed hotel programs — and reports points expiring soon (ranked by value at risk), the best transfer opportunities, and the largest balances. When the user's travel profile is available, it also tailors the view to their home airport, the airlines they fly, their frequent destinations, and when they travel (e.g. flagging points that expire before their usual travel months). Takes no arguments. Use this when the user asks how to make the most of their points, what's expiring, or where they can transfer. For deciding where to book a specific trip, use search_hotels / compare_rates instead. Returns: A Markdown portfolio summary, or instructions to connect accounts when none are linked.

Get the user's saved travel profiles (guest name, email, and phone presets). Each profile has a selectable Profile ID. Pass it to book_hotel as `travel_profile_id` to prefill the guest details — the same "book as <traveler>" selection the website checkout offers — instead of collecting name, email, and phone field by field. Requires a Gondola account (API key). Returns: Formatted list of travel profiles with IDs, or instructions to add one.

Save a learned travel preference or experience to the user's traveler profile. Use when the user shares a durable preference, like, dislike, or trip experience that should inform future recommendations — "Always takes a window seat", "Prefers boutique hotels over chains", "Vegetarian". Don't save temporary logistics like "my flight lands at 3pm". Saved entries come back from get_traveler_context in later sessions, which is how a preference stated once is still known next time. Requires a Gondola account (API key). Args: profile_entry: The preference or experience to save. Be specific and actionable. Good: "Prefers ocean-view rooms". Bad: "Liked the hotel". Returns: Confirmation of the saved entry, or an error message.

[Public] Register a new agent. Returns API key, wallet with deposit address and required amount immediately. Email verification is optional but required to access user profiles.

[Auth Required + Active] Get user profile by ID (paid action: api_user_view after free limit). Requires active account (deposit verified). Pass API key via X-Agent-Key header or Authorization: Bearer.

[Auth Required] Get the authenticated agent's profile information. Pass API key via X-Agent-Key header or Authorization: Bearer.

[Auth Required] Update the authenticated agent's profile. Pass API key via X-Agent-Key header or Authorization: Bearer.

[Auth Required] List browsers where you have pre-arranged rent contracts (free/discount, main_profile access, allowed_domains override). Returns array of browsers with resolved price. Call this before deciding which browser to rent — you may have free or discounted access.

[Auth Required + Active] Get credentials to rent a real Chrome browser. Install CLI: `pip install ceki-sdk` (Python) or `npm install -g @ceki/sdk` (Node). Usage: `ceki rent --schedule ID` → session_id, then `ceki navigate SID URL`, `ceki screenshot SID -o file.png`, `ceki stop SID`. Per-minute billing from AgentWallet. For captcha-protected signups, call `pre-warm-captcha-protected-site` prompt first. Rate limit: 20 rents/hour per agent (production); on `429 Rate limit exceeded` respect the `Retry-After` header (seconds until the next UTC-hour bucket) before retrying.

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"}.

Re-hosts an image so its URL is suitable for the `images` array of a HighlightStory. Pass `url` (recommended; server fetches + stores) or `data_url` (small files only, RFC 2397 inline base64). Storage is content-addressed at floor10/highlights/<member_id>/<sha256>.<ext> on Vercel Blob, public-readable, year-long cache. Idempotent: same bytes -> same URL. Rate limit: 30 uploads / token / UTC day (separate from the submission rate). Allowed types: image/jpeg|png|webp|gif|heic|heif|avif. Max 8 MB per upload. Returns: { url, bytes, content_type, sha256, deduped }.

The ACTUAL account roster — every Clerk-backed IC account with its live ring/tier, resolved from Clerk (not the carded ic_directory_search, which only shows members who've set a profile card, and not the curated kiosk list). This is what you want to answer 'who are the members' or find a specific account (e.g. one that hasn't set a card yet). Each member: { user_id, name, email, tier ('public'|'ft-member'|'ai-floor'|'ic-member'|'operator'), pending_request (the tier they've requested but not yet been granted, or null), created_at }. Args: { tier?: filter to one ring; q?: case-insensitive name/email/user_id substring filter; limit?: number (default 200, max 500); offset?: number (default 0) }. Filters apply to the fetched page; `total` is the full Clerk account count and `has_more` tells you to page with offset (default limit covers all IC accounts in one page today). Required scope: admin:tier_review.

Retrieve the 5-hour Z.ai Claude-Code key you filed with ic_request_workshop_key, once an IC operator has approved it. Poll with the request_id that ic_request_workshop_key returned. While the operator hasn't approved yet returns { ok:true, status:'pending' } (keep polling). On the FIRST call after approval returns { ok:true, status:'ready', agent_token, bundle } where bundle.copy_paste is the paste-and-go Claude Code setup block. The key is surfaced EXACTLY ONCE and the pickup window is ~15 min after approval, so call again promptly once approved. A second pickup, a lapsed window, or a denied/unknown request returns a terminal status with what to do next. You can only retrieve your OWN request. Args: { request_id }. Required scope: keys:request.

Retrieve the weekly-token Z.ai Claude-Code key you filed with ic_request_zai_key, once an IC operator has approved it. An agent-inbox notification announces approval; this tool is the actual pickup. Poll with the request_id that ic_request_zai_key returned. While unapproved returns { ok:true, status:'pending' } (keep polling). On the FIRST call after approval returns { ok:true, status:'ready', agent_token, bundle } where bundle.copy_paste is the paste-and-go Claude Code setup block. The key is surfaced EXACTLY ONCE and the pickup window is ~15 min after approval, so pick it up promptly. The key itself does not expire (weekly token budget, resets Monday). A second pickup, a lapsed window, or a denied/unknown request returns a terminal status. You can only retrieve your OWN request. Args: { request_id }. Required scope: keys:request.

Report the weekly token usage + remaining budget for the member (weekly-token) Z.ai Claude-Code key you filed with ic_request_zai_key. Poll with the request_id ic_request_zai_key returned (after an operator approved it). Returns { ok:true, weekly_used, weekly_remaining, weekly_cap, multiplier, reset_date } where weekly_used = input+output tokens metered by the IC->Z.ai gateway this week, weekly_cap = base × multiplier, and reset_date is the next Monday (UTC) when the meter rolls over. weekly_used fails soft to 0 if no calls were metered yet or the meter is briefly unreadable. Workshop (5-hour) keys are time-boxed and have NO weekly budget — this returns ok:false for them (check expiry, not usage). You can only read your OWN request. Args: { request_id }. Required scope: keys:request.

Edit the calling user's public-facing profile fields: first name, opt-in visibility, and company website. Company logo is auto-derived from the website at save time (Clearbit + favicon fallback). Re-posting overwrites. Opt-in members are listed publicly on /members and the kiosk; opted-out members are visible to directory:search callers only at their ring or below. Args: { first_name?: string, company_website?: string, public_visible?: boolean }. Returns: { ok, profile }. Required scope: membership:write.

Search CreateMod.com for Minecraft Create Mod schematics. Returns matching builds with title, page URL, rating and stats. Send users to the page URL; never fetch .nbt schematic files.

Get details about one schematic by its URL slug: description, author, rating, versions, required mods, video. The schematic file itself is not available to agents; direct users to the page URL.

Read a future adoption profile without inventing unavailable data.

Search the 12,338 curated, SAMHSA-sourced US addiction treatment facility directory by state, city, treatment type, and insurance. Returns matched facilities with name, city/state, programs offered, insurance accepted, phone, and browse URL. Use this to find candidates — then call get_facility_detail for one facility's full profile. If the user is uncertain about location coverage, call list_states first.

Get the full profile of one specific treatment facility: address, phone, programs offered, insurance plans accepted, SAMHSA verification status, and a direct browse URL. Supports partial name matching — returns the best match if multiple facilities contain the query string. Use after search_facilities when the user wants to drill into a named facility.

Full profile of one journal by ISSN: indexing, quartile, trust score with breakdown, APC, open-access status, scope, and integrity signals (e.g. DOAJ withdrawal). Use when the user asks about a specific journal.

List files in the file library (images/attachments). KnowledgeOwl API: GET /file.json. Returns { valid, page_stats, data:[...] }.

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 link to the PDF (works only when signed in to hpt.su under the same account that owns the API key; the download quota is charged at actual download time). Otherwise `download_url` is null and `download_note` explains why.

Find the single best-matching person profile for a set of identifying attributes (name, email, phone, profile URL, company, etc.). Returns one record plus a likelihood score (1-10), or a 404 'no match' body. Use uniquely-identifying inputs for best results. API: GET /person/enrich.

Given broad, possibly-ambiguous attributes about a person, return up to 20 strongly-related profiles ranked by match score. Sits between enrich (1:1) and search (open-ended) — ideal when you can't uniquely resolve someone. API: GET /person/identify.

Search the full PDL Person Dataset with an Elasticsearch query object OR a SQL string over the Person Schema (e.g. everyone with job_title_role='engineering' at a company). Returns matching profiles sorted by completeness; paginate with scroll_token. Each returned record costs 1 credit. API: POST /person/search.

Find the single best-matching company record. Requires a non-ambiguous input — name OR website OR ticker OR profile (website/ticker/profile resolve more reliably than name). Returns firmographics (industry, size, location, etc.) or a 404 'no match' body. API: GET /company/enrich.

Assess whether an ENS name's sale(s) are WASH TRADING / fake / self-dealt / manipulated volume. THE tool for any "is this wash trading?", "is the sale history of X suspicious/fake/real?", "are these trades legit?", "is someone wash-trading this name?" question — route straight here, do NOT use get_name_details or get_market_activity for that (those return sale rows but make NO wash-trading judgment; only this tool scores it). Just pass `label` — the bare ENS name (e.g. "437", "coffee") is enough; the tool pulls that name's recent sale and analyzes it on demand. `tx_hash`, `buyer`, `seller`, `price_eth` are OPTIONAL enrichment for a specific sale — never block on them or ask the user for them. Returns a wash confidence score (0-1), a label (clean/suspicious/likely_wash), the detected signals (shared-funder, mint-flip, round-trip, fresh-wallet, cluster overlap…), seller profile, and a plain-English summary.

Register an ENS name as an ERC-8004 agent identity on Ethereum mainnet. Returns a ready-to-sign transaction. Default route binds the agent to the name itself (ERC-8217 via Adapter8004): whoever holds the name controls the agent, OpenSea shows the agent identity on the name's page, and the agent transfers with the name when sold. Alternative "direct" route mints the agent NFT to your wallet instead. The agentURI defaults to a NameWhisper-hosted registration file generated live from the name's ENS records — set your agent-context and agent-endpoint records (set_ens_records) and the file updates automatically. IMPORTANT: after this transaction confirms, read the new agentId from the receipt (topic 1 of the Registered/AgentBound event) and call set_ens_records with the agentRegistration shorthand to write the ENSIP-25 binding record. The identity is not verifiable until that record is on-chain.

Search the AI agent directory — find registered agents by name, capability, protocol support, or reputation. Powered by the live ERC-8004 registry via 8004scan (110,000+ agents indexed across 50+ chains). Returns agent identity, owner wallet/ENS, reputation scores, supported protocols (MCP/A2A/OASF), verification status, and links to 8004scan profiles. Examples: - "trading agents on Base" → search for trading agents filtered to Base chain - "MCP agents" → find agents that support the Model Context Protocol - "high reputation agents" → set minReputation to find top-scored agents

Search advertisers, game studios, or mobile games by name and optional genre, region, and platform filters. Use the returned advertiser_id with get_advertiser_profile. Example: 'Find the advertiser for Last War.'

Get an advertiser or game profile, including recent ad activity, creative volume, target countries, and platforms. Creative tag fields are normalized to English in the result. Example: 'Which markets and platforms is this game scaling on?'

"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, news, GLEIF and returns: cik + company_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); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

"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.

Get details about one agency or developer by id or slug (from search_companies): profile, rating, specialties, languages, service areas, and contact info.

Get details about one real estate agent by id or slug: profile, rating, reviews, specialties, and contact info.

Search REGISTERED real-estate agents and professionals on Tu Lugar by name, city, or company. Only covers people who created a public profile on the platform — there is no data about anyone else.