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680,563 tools. Updated 2026-10-20 09:52

"A guide for data cleaning and analysis in Excel" matching MCP tools:

  • Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.
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  • Order a formatted, downloadable financial report (Excel or PDF) for a Norwegian company — the same multi-source-fused figures, layout and source note as the report a customer would download in the Firmaradar portal, ready to file or forward. Returns a short-lived download link + metadata (years covered, source, currency), NOT the file itself and NOT base64 data — fetch the download_url separately, no further auth required, within expires_in seconds. Use `get_company_financials` instead when you need the raw figures to reason about, not a document to hand off. Requires the Excel-export or PDF-export add-on (matching the requested format) on the caller's account. Charges 1 credit per financial year included in the report.
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  • Create a booking policy. Call get_booking_rules FIRST and reuse a matching set instead — these are shared company-wide, not per product. `weeklyHours` are LOCAL wall-clock times at the outlet; if neither the outlet nor the company has a timezone the engine refuses availability with a 400, so fix the outlet rather than guessing an offset. `bufferMinutes` consumes grid time for slot bookings (cleaning between appointments); for overnight stays use checkInTime/checkOutTime instead and leave the buffer at 0 — the cleaning window lives in the gap and does not consume a night.
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  • Use when someone needs a published Rung occupation, resume-situation, or military-transition guide. Returns public guide facts, source pages, and browser handoffs. Do not use for live jobs, employer search, resume editing, qualification decisions, or private work history; never send personal or resume data.
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  • AZURE DEVOPS ONLY -- Reads the ACTUAL CONTENT of a file attached to a work item (Excel spreadsheet, Word document, text/CSV/JSON/XML file, or image). WHEN: a work item (FDD/RDD/CR/Bug/Task/User Story) has an Excel/Word attachment with requirements, field mappings, mockups, or specs that need to be read to understand the ask. Triggers: 'read the attachment', 'open the excel file on the work item', 'what does the attached document say', 'lis le fichier joint', 'ouvre l'excel du ticket'. Call ado_analyze_workitem first (or ado_query_workitems) to discover attachment file names if you don't already know the exact fileName. Supported: .xlsx/.xlsm (returns sheet names + a markdown table of the requested/first sheet), .docx (returns extracted markdown text + tables), .txt/.csv/.json/.xml/.md/.log (returned as-is), images (.png/.jpg/.jpeg/.gif/.bmp/.webp, returned as a base64 data URI for visual analysis, max 4 MB). Other binary formats (PDF, .pptx, .zip, etc.) are NOT parsed -- returns metadata + a manual download link instead. Max attachment size read: 25 MB. Requires DEVOPS_ORG_URL + DEVOPS_PAT env vars.
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  • Fetch Yahoo Shopping homepage editorial cards, including title, link, category, and thumbnail. This is a buying-guide and deals feed, not product search; use yahoo_shopping_category for a section, yahoo_shopping_article for one guide, or yahoo_shopping_store for one retailer's offers.
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  • India Open Government Data (OGD) Platform MCP — data.gov.in

  • Free US cleaning cost, time, crew, and chemical-use calculators with visual reports.

  • Download a German PDF guide: 7 legal side-income routes in Switzerland. Use when a Swiss/German-speaking human wants a guide. Not for agent automation (use the JSON tools). Returns a free sample plus the paid URL and pay steps (no charge here); the full result costs $17 Base USDC via x402.
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  • Fetch Yahoo Shopping homepage editorial cards, including title, link, category, and thumbnail. This is a buying-guide and deals feed, not product search; use yahoo_shopping_category for a section, yahoo_shopping_article for one guide, or yahoo_shopping_store for one retailer's offers.
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  • Download any Rent Manager report. Format selection rules — IMPORTANT: • **PDF is the default for downloads.** If the user says "download the report", "send me the report", "give me a copy of X", "I want X for my records", or any similar phrasing without naming a format → leave ``format`` unset (defaults to pdf). • **For ANY Excel-related request, use ``xls`` (NOT xlsx).** This includes: "Excel file", "spreadsheet", "in Excel", ".xls", "Microsoft Excel", "give me an XLS", "Excel version", and any similar phrasing. Rent Manager renders xls with much nicer formatting (column widths, headers, group totals) than xlsx, so xls is the preferred Excel format for this product. • **Only use ``xlsx`` when the user explicitly types "xlsx"** — e.g. "download the P&L as xlsx" or "give me the .xlsx file". Any other Excel phrasing → xls. • ``csv`` (or json / txt / html / xml) only when the user wants to *see* the data in chat — those small text formats are inlined into the response so the model can read them directly. Phrasings like "show me", "display", "what's in X", "summarize X" → csv. Available formats: ``pdf`` (default), ``xls``, ``xlsx``, ``excel`` (alias → xls), ``spreadsheet`` (alias → xls), ``csv``, ``json``, ``txt``, ``html``, ``xml``. Output behavior by format: • **csv / json / txt / html / xml** — small files (≤1 MiB) are ALSO inlined in the response so the model can read the contents directly. • **pdf / xlsx / xls** — saved to the per-tenant file store and returned as a signed ``/files/<id>?sig=...`` URL the user can click directly in chat. For analytical questions prefer the ``analyze_*`` wrappers — they're faster and return computed answers directly. For any P&L / Profit and Loss / T12 request use ``analyze_pl_trend`` (12-month recap report, the default P&L view). Custom ReportWriter reports: set ``report_writer=True`` to download a custom report from RM's ReportWriter (the IDs shown as kind "rw" in ``list_reports(live=True)``). These live in a separate ID namespace that collides with the canned reports, so the flag is required to disambiguate. They carry their own saved filters and run portfolio-wide; pass any ad-hoc parameters via ``extra_params``. (The ``start_date``/``end_date``/ ``property_id``/``portfolio`` scoping args do NOT apply to ReportWriter reports.)
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  • START HERE for any open-ended request. Lists the task playbooks this server supports — systematic learning from bookmarks, organising into themes, cleaning up, X-list intelligence, exporting data out, finding a half-remembered save, digests, and diagnosing sync. Each names when to use it; call get_skill for the exact tool sequence.
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  • Use this when a veteran asks about a VA topic VeteranHQ has written a guide on. It searches only the VeteranHQ guide library and reads no account data, so the answer is the same for every caller with the same inputs. Returns the guides whose text matches the query, highest scoring first, each carrying the guide slug, title, summary and public URL, and no body text. The ordering is lexical and deterministic, computed from where each word of the query appears: a match in the guide title scores above one in the summary, a summary match above one in a section heading, and a heading match above one in the body, with an added score when every word of the query appears somewhere and a further one when the whole query appears in a title. Guides tied on score are ordered by slug, so the same query returns the same list in the same order on every call. No model runs and no network call is made. The limit parameter caps how many guides come back, from 1 to 10, default 5. An empty results array means no guide in this library contains any word of the query, which is a fact about the library and not about VA rules or about what VA holds. Reading one is a second call: pass a returned slug to get_guide.
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  • Use this when a veteran needs what a VeteranHQ guide on a VA topic says, given a slug from search_guides. A guide states the rules as VeteranHQ read them from the cited sources on the date it reports, and only VA decides a claim. Returns the slug, title and summary, the date the facts in it were last verified against its sources, the public URL of the guide on veteranhq.app, the body split into the sections the guide itself defines, each with a heading and its text, and the sources the guide cites, each with a title and a URL. A slug this library does not hold returns a tool error carrying GUIDE_NOT_FOUND, whose message says to call search_guides and use a slug from its results. A guide longer than one result can carry returns the sections that fit, plus omittedSections counting the sections left out and a note stating that count and the guide URL. A single section larger than the whole budget is served shortened at a paragraph or sentence boundary, with truncatedSection naming its heading and the note repeating it, so a section that was cut is distinguishable from one served whole. Those three fields are absent when the whole guide is returned, so a shortened answer is distinguishable from a complete one. It reads no account data, so the answer is the same for every caller with the same inputs.
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  • Return Genpio's guide for one country or market: what that market's platforms allow for an AI livestream host, quoted from their own policies with links, which local platforms Genpio does not stream to, which languages Genpio Voices speaks there, and the guide's full text as Markdown. Use it whenever a question names a country, and pass the language the person is writing in so the guide comes back in it. For a country without a guide it says so and gives only what holds worldwide; do not carry another country's platform rules over to it. With no country, it lists every guide.
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  • Start an E-E-A-T analysis on a guide's top SERP competitors Starts an asynchronous E-E-A-T analysis on the top competitors of the guide's SERP. Each competitor is fetched and scored individually. Use GET /api/v1/eeat-competitors to poll for results until `pending` reaches `0`. **Token cost:** This endpoint charges `eeatCompetitorsTokensCostPerCompetitor` (see /api/v1/tokens-usage) per competitor analyzed, up to 10 competitors. Example: 10 competitors × 5 tokens = 50 tokens. 6 competitors × 5 tokens = 30 tokens. The number of competitors corresponds to the deduplicated URLs in the guide's top-10 SERP results (available via GET /api/v1/guide).
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  • Open-ended crypto and DeFi analysis from Einstein's full research stack — use this when no more specific tool fits, or when the question spans several domains. Returns a written analysis grounded in live on-chain and market data. [Paid: $1.00 per call from your Einstein credit balance. Free alternatives exist for several of these — see list_einstein_capabilities.]
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  • Returns the exact cleaning rules (how emails, phone numbers and URLs are detected and normalized), the dedup modes and keep strategies, the order the steps run in, and the maximum rows per call. Call this first if you are unsure how a field will be treated. Free, processes no data.
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  • Returns a consolidated, copy-paste-ready Markdown system prompt of SMI Aware house rules and a when-to-call-which-tool routing guide, plus exact paste-in locations for Claude Projects/Cowork/Desktop, Cursor, and other clients, so the assistant calls the right smi_* tools automatically. Runs locally; makes no network calls and takes no case data.
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  • Every cottage's price for a stay, whether it is free, and whether it sleeps the party. The figures are before the cleaning fee and taxes: quote_trip gives the all-in total.
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  • Use this when the user wants a table turned into an Excel spreadsheet (.xlsx) or a CSV file: "convert this PDF table to Excel", "make this into a spreadsheet", "export to CSV", "PDF to Excel", "screenshot to Excel". First read the table yourself from the uploaded file, image or text, then pass the header row and every data row exactly as written (keep currency signs and minus signs; do not total or reorder). Returns download links for .xlsx and .csv and a preview.
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  • List available cleaning slots. Saturdays and Sundays only, 8 AM – 6 PM PT, San Francisco only. Omit `date` for the next 8 upcoming weekend days.
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  • Mint a short-lived signed URL for a frozen workbook version (the Excel file). Give the URL to your user to open in a browser — it needs no login and expires in about 10 minutes. The bytes are immutable and integrity-hashed.
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