"Raspberry Pi" matching MCP tools:

• strale_execute

  Strale - 290+ API capabilities for AI agents

  Executes a Strale capability by slug and returns the result. Use this when you need to perform any verification, validation, lookup, or data extraction from the 271-capability registry. Call strale_search first to find the right slug and required input fields. Returns a result object with the capability output, quality score (SQS), latency, price charged, and data provenance. Five free capabilities work without an API key (10/day limit). Paid capabilities debit from the wallet — check strale_balance first for high-value calls.

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• search_grants

  Scite

  Search research grants from the scite grants database (NIH RePORTER, NSF, SBIR/STTR, Wellcome, EU, and more). Use this tool to find grants by research topic, PI, organization, agency, or funding keywords. Returns grants with title, a short abstract preview, agency, organization, PI, country, dates, awardAmount, tags, and externalLink. Highlighted `<strong>...</strong>` fragments indicate which fields matched the query. **Grouping.** Resolute groups related grants under one shared slug (e.g. NIH subprojects of one center grant, or renewals of the same award). Each search result returns **only one representative grant** per group. `grantsInGroup` tells you how many total grants exist in the group; `siblingGrantIds` (when present) lists the other grant ids in the group. To pull the full record for a specific sibling, call `get_grant` with its id — do not re-search. **Abstract in search is a ~300-char highlighted preview, not the full text.** Call `get_grant` when you need the full abstract (often 1-3 KB) or source-specific identifiers (`awardYear`, `agencyTrackingNumber`, `contract`, `nihProgramCode`, `nihrApplicationId`). If the search result already contains the fields you need, do not call `get_grant`. **Parameters:** - q: Search query string (keywords, PI name, organization, agency, etc.) - f: Space-delimited filters in `field:"value"` format (e.g. `agency:"NIH" country:"United States"`) - p: Page number (default: 1) - s: Sort field (default: _relevance). Options: - _relevance: relevance score (sortDir ignored) - awardStartDate: grant start date - awardCloseDate: grant close date - awardNoticeDate: grant notice date - awardAmount: total award amount - employeeCount: PI employee count - sortDir: Sort direction, asc or desc (default: desc). Ignored when s is _relevance. **Returns:** Grants with id, title, abstract snippet, agency, organization, piName, country, award dates, awardAmount, tags, groupSlug, and grantsInGroup.

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• ai

  Fast.io

  Ripley — the MCP delegation surface over Fastio's RAG agent. Ripley is read-only for storage CONTENT: it answers natural-language questions about workspace/share files & folders (with citations) and never creates/edits/deletes your files — for content writes, call the primitive MCP tools directly. It DOES create/manage chat threads (chat-create/chat-update/chat-delete/message-send) and can generate shares (share-generate). Prefer Ripley over issuing many primitive reads: ask one NL question and let the server-side agent search + synthesize. Quick start: action='ask' (question + profile) → returns {answer_text, citations, chat_id, message_id, web_url}; action='status' for an engineered workspace-status summary. Lower-level chat/message actions remain for multi-turn control. Call action='describe' for the full action/param reference. Destructive: chat-delete. Side effects: ask/status/chat-create/message-send consume credits; chat-cancel terminates an in-progress message (partial tokens billed; idempotent). Verbosity (detail param): chat-list/message-list default to terse (compact rows). chat-details/message-details default to full (drill-down). Pass an explicit detail='standard'|'full' to override (best-effort: chat/message/activity endpoints may not yet honor detail server-side).

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• verify_claim

  срезAI — Search API for AI agents

  Проверяет утверждение: ищет источники, читает несколько независимых страниц и возвращает вердикт с дословными цитатами. Каждая цитата сверена с текстом страницы — не найденная в тексте отбрасывается вместе со своим доводом. Когда: факт, который нельзя брать на веру — цифра, дата, «X поддерживает Y», утверждение из ответа пользователя или из вашей же памяти. Особенно если ваш контекст не вмещает 4–5 страниц целиком: вся черновая работа делается на нашей стороне, к вам приходят только вердикт и цитаты. Когда не: нужен обзор темы — deep_research; нужен текст конкретной страницы — read_url. Вердикт: supported — источники подтверждают; refuted — опровергают; mixed — расходятся между собой; unverified — подтверждения не нашлось. Последние два — нормальный результат, а не ошибка: значит, утверждение нельзя считать проверенным. Считает в независимых доменах: три цитаты с одного сайта — один голос. Смотрите agreeing/disagreeing и confidence, а не только вердикт. Возвращает: вердикт, уверенность, цитаты со ссылками и оговорки. Источников — 2–5. Время: 15–60 с / 15–60 s. Цена: 8 кредитов (поиск, чтение источников и работа модели). Verifies a statement: searches for sources, reads several independent pages and returns a verdict with verbatim quotes. Every quote is checked against the page text — one that is not found there is dropped along with its argument. Use when: a fact you should not take on trust — a number, a date, "X supports Y", a claim from the user or from your own memory. Especially when your context cannot hold 4–5 pages at once: the legwork happens on our side, you receive only the verdict and the quotes. Do not use when: you need an overview of a topic — deep_research; you need the text of one specific page — read_url. Verdict: supported — the sources confirm it; refuted — they contradict it; mixed — they disagree with each other; unverified — no confirmation was found. The last two are normal outcomes, not errors: they mean the claim cannot be treated as verified. Counted in independent domains: three quotes from one site are one voice. Read agreeing/disagreeing and confidence, not just the verdict. Returns: verdict, confidence, quotes with links and caveats. Sources: 2–5. Time: 15–60 с / 15–60 s. Cost: 8 credits (search, source reading and model work).

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• ask_pipeworx

  Ip Api

  PREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring authoritative structured data with citations. Routes the question to the right one of 5,462 tools across 1419 verified sources, fills arguments, returns the structured answer with stable pipeworx:// citation URIs. Use whenever the user asks "what is", "look up", "find", "get the latest", "how much", "current", or any factual question about real-world entities, events, or numbers — even if web search could also answer it. Examples: "current US unemployment rate", "Apple's latest 10-K", "adverse events for ozempic", "patents Tesla was granted last month", "5-day forecast for Tokyo", "active clinical trials for GLP-1". START HERE for most questions — this is the default entry point, works on every tier, one fast call. Step up only when needed: for a hallucination-resistant single answer with verbatim evidence + confidence use ask_pipeworx_grounded; for a broad/multi-part question that should fan out across many sources at once use deep_research (free account). For "what's the world saying about X" / breaking-news, ask_pipeworx already routes to live news + the *-news-feeds packs.

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• deep_research

  Ip Api

  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 1419 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 5,462 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 — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "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).

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• arena_get_cycle

  Backtesting Arena

  Crypto cycle position — where are we in the cycle? Default BTC: point-in-time 10-indicator aggregation (MVRV-Z, NUPL, Puell, Pi-Cycle, Funding, Hash-Ribbons, Power-Law, Rainbow, F&G, Mayer). Pass asset=ETH or asset=SOL for a per-coin cycle read built from the transferable price-derived indicators (Mayer, weekly-RSI, 200-week-MA distance) with renormalized weights; BTC-native indicators (halving, dominance, mining, hash-ribbons, F&G, Pi-Cycle, on-chain) are explicitly returned as `not_applicable` rather than faked. All return raw + Z-Score, signal enum, and a `percentiles` block ranking each indicator against that asset’s own history. The `signal` enum is a FIXED SCORE-BAND LABEL (<25 accumulation · 25–45 recovery · 45–60 expansion · 60–75 distribution · ≥75 overheated), not an independent market-phase detection — a mid-band score reads "expansion" even in a drawdown market (the 45–60 band is the neutral middle; cross-check price/drawdown context before quoting the label as a market state). BTC additionally returns `highlights[]` (rule-based markers for currently unusual indicator values — descriptive, versioned ruleset, no direction or advice; empty array = nothing unusual) and `price_context` (price at scoring time vs live spot with drift % — the scores are based on the scoring-time price, not the live spot). Point-in-time scored — not reconstructable from a generic price API. Note for volatility questions: this tool carries the regime context around a volatility reading (Funding, Mayer, Pi-Cycle) but not the volatility series itself — that is arena_get_volatility_history. Related: arena_get_historical_analog (what followed states like this one), arena_get_bullmarket_ampel, arena_get_pulse. [Free tier]

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• read_url

  срезAI — Search API for AI agents

  Открывает одну страницу по известному адресу и возвращает её текст чистым markdown — без навигации, рекламы, скриптов и HTML. JavaScript выполняется на нашей стороне, поэтому SPA тоже читаются. Когда: адрес известен и нужен текст — статья, документация, карточка товара. Когда не: адреса нет — сначала web_search; страниц несколько — read_urls (один вызов вместо пяти); нужны 2–5 конкретных полей — extract (в контекст придут только они); нужно увидеть вёрстку — fetch_page. Возвращает: заголовок и текст, по умолчанию первые 4000 символов. Длинная страница приходит по частям: в конце ответа указано значение offset, с которым надо вызвать тул повторно, чтобы получить продолжение. Так документ любого объёма читается окнами под ваш контекст, без повторной оплаты уже прочитанного. Цена: 1 кредит, самый дешёвый способ получить содержимое страницы (fetch_page — 3). Opens a single page by a known URL and returns its text as clean markdown — no navigation, ads, scripts or HTML. JavaScript is executed on our side, so SPAs read fine too. Use when: you have the URL and need the text — an article, documentation, a product page. Do not use when: you have no URL — start with web_search; you have several pages — read_urls (one call instead of five); you need a handful of specific fields — extract (only those reach your context); you need to see the layout — fetch_page. Returns: title and text, the first 4000 characters by default. A long page arrives in windows: the end of the response states the offset to call the tool with again to get the continuation. That way a document of any size is read in windows sized to your context, without paying twice for what you already read. Cost: 1 credit — the cheapest way to get page content (fetch_page costs 3).

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• strale_ping

  Strale - 290+ API capabilities for AI agents

  Checks that the Strale API is reachable and the MCP server is running. Call this before a series of capability executions to verify connectivity, or when troubleshooting connection issues. Returns server status, version, tool count, capability count, solution count, and a timestamp. No API key required.

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• strale_getting_started

  Strale - 290+ API capabilities for AI agents

  Lists the free capabilities available without an API key and explains how to get started. Call this on first connection to see what you can do immediately. Returns 5 free capability slugs (email-validate, dns-lookup, json-repair, url-to-markdown, iban-validate) with descriptions, example inputs, and instructions for accessing the full registry of 271 paid capabilities. No API key required.

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• get_clinical_trial

  Scite

  Fetch full details for a single clinical trial by NCT id. Use this after `search_clinical_trials` when you need the complete record for a specific trial, including the full `description`, study `design`, `enrollment`, `outcomes` (primary/secondary), full `eligibility` inclusion/exclusion criteria, `reportedEvents` (adverse events when the trial has posted results), principal investigator (`pi`), `contacts`, `citations` (related publications), and `resultsUrl`. The search tool returns a slim summary to save tokens; call this tool for a specific NCT id when you need those verbose fields for deeper analysis or patient-trial matching. **Parameters:** - id: NCT identifier (e.g. `NCT02986230`). **Returns:** A compact detail record preserving all trial fields except the low-signal `ontology` classifications.

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• validate-pn

  PartsTable

  Validate a part number against known manufacturer format rules. Returns structural validity, matched format rule, and warnings. IMPORTANT: Format validation only - does not confirm the part exists.

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• ask_pipeworx_beta

  Ip Api

  Beta version of ask_pipeworx: identical universal router (same 5,462 tools, same arguments, same response shape) with candidate routing improvements enabled live whenever one is under test. No candidate is active right now (the last was retired on outcome evidence 2026-07-26), so this currently matches ask_pipeworx exactly. Use it exactly like ask_pipeworx when you want the newest routing; results are compared against the stable router to decide what merges. Falls back to nothing — this IS a full working router, just the experimental edge.

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• nausika_calculator

  Nausika

  Evaluate a math expression and return the numeric result. Useful for fuel, range/autonomy, unit conversions, and ad-hoc arithmetic. Supported (exhaustive): +, -, *, /, ^, %, parentheses, sqrt(), abs(), ceil(), floor(), round(), sin(), cos(), tan(), log(), exp(), min(), max(), PI, E. Anything else (atan2, pow, log10, hypot, if, factorial, comparisons) is rejected. Examples: "(120 / 6) * 8.5" (fuel for 120 nm at 8.5 L/h, 6 kn); "45 * 1.852" (nm to km).

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• search_awards

  Nsf Awards

  Search NSF awards. Filter by keyword (matches title/abstract), PI name, awardee institution, NSF program, date range, US state, or country. Returns title, PI, awardee, amount, dates, program. Use get_award for full abstract + outcomes report.

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• calculate

  utility-converter

  Safely evaluate an arithmetic expression and return the exact result. Supports +, -, *, /, //, %, ** (power), parentheses, the constants pi and e, and the functions sqrt(), abs(), round(). Does not execute arbitrary code.

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• ai-extract-batch

  x402 Bazaar

  Same fields across up to 10 texts, one payment — The pipeline version of ai-extract: send up to 10 documents (text1=…&text2=… or texts= with ||| separators) and one field list — get one schema-enforced JSON object per document, in order, from a single paid call. 10 extractions for $0.10 instead of 10x the per-call overhead: built for agents parsing feeds, inboxes, scrape batches and receipt piles. Up to 6K chars per document. Required input: text1. Priced $0.10 per call over x402 on Base; send a prepaid x-credit-token header for unlimited calls, or get 1 free call/day per tool. No wallet or API key required.

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• calculate

  Bay Run

  Evaluate arithmetic/math EXACTLY and instantly — the reliable calculator agents need because LLMs silently botch multi-step arithmetic. SAFE: no code execution, a hardened whitelist parser (not eval). Supports + - * / // % **, parentheses, and common math functions/constants (sqrt, log, log10, exp, sin/cos/tan, floor, ceil, abs, factorial, pi, e, tau). Returns {ok, result} or {ok:false, error}. Deterministic, sub-millisecond.

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• Get-Upload-API-Info

  YouCam for Beauty & Personal Care

  Returns the upload API endpoint and example request/response for uploading images (JPEG, PNG) or videos (MP4) to YouCam AI./n Use when the user wants to upload an image/video via the API. If upload cannot be completed for any reason (including network restrictions, host_not_allowed, or other errors), do not retry. Immediately use the File Upload Widget instead. Do not ask the user for a public URL.

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• explain_denial

  DenialPath

  Explain a CARC (Claim Adjustment Reason Code) and any RARCs (Remittance Advice Remark Codes) from a remittance: plain meaning, ranked corrective actions, and whether an appeal is worth filing. found:false means we do not hold that CARC in our dataset (X12 publishes far more codes than we have curated) - the response still returns the group-code meaning when a group prefix (CO/PR/OA/PI) was supplied, and note explains the gap rather than leaving it silent. unknownRarc reports, rather than silently drops, any RARC you passed that we do not hold. Passing payer additionally attaches that payer's appeal deadline where we hold one. Free, no API key needed.

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