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754,864 tools. Updated 2026-11-07 07:03

"MCP servers for reading and parsing PDF, Word, and PowerPoint documents" matching MCP tools:

  • Publish a PDF, Word (.docx), PowerPoint (.pptx), Excel (.xlsx/.xls), or CSV file as a browser-viewable page, private by default. Accepts filename and base64 content, up to 4 MB decoded. Documents become readable PDFs, slides have presentation controls, and spreadsheets have searchable sheet tabs. Preserves the original for download. A siteId replaces the page at the same address. Does not send invitations.
    Connector
    Destructive
    No auth
  • Publish a PDF, Word (.docx), PowerPoint (.pptx), Excel (.xlsx/.xls), or CSV file as a browser-viewable page, private by default. Accepts filename and base64 content, up to 4 MB decoded. Documents become readable PDFs, slides have presentation controls, and spreadsheets have searchable sheet tabs. Preserves the original for download. A siteId replaces the page at the same address. Does not send invitations.
    Connector
    Destructive
    No auth
  • Convert Word, Excel, PowerPoint, OpenDocument and other office files to PDF (LibreOffice). Files go in as links; use upload_file first for a file on the user's computer.
    ConnectorAPI key
  • Convert an office document (Word, Excel, PowerPoint, ODT, and many more) at a URL to a PDF using LibreOffice. Returns a { FileUrl } (valid ~24h). BILLED. Api2Pdf API: POST /libreoffice/any-to-pdf.
    Connector
    Destructive
    No auth
  • Text of a document (PDF, Word, Excel, PowerPoint …) page by page ("[Page n]"), so you can answer questions about it or summarize it. Long documents: read on from next_start_page, or pass a page range.
    ConnectorOAuth
  • A file's words, up to 5 MB: text, PDF, Word, Excel and PowerPoint files are read in a separate, capped process. Free. Free.
    ConnectorOAuth

Matching MCP Servers

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    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
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Matching MCP Connectors

  • Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.
    ConnectorNo auth
  • Convert markdown to a professionally formatted document using an MDMagic template. IMPORTANT GUIDANCE: 1. Output format → what user gets: - 'docx' → a single Word .docx file - 'pdf' → a single .pdf file - 'html' → a single .html file - 'all' → a ZIP containing all three (DOCX + PDF + HTML) 2. If the user is ambiguous (e.g. 'convert this'), ASK which format they want before calling. Don't assume. 3. Filename: if the user attached a file (e.g. 'mydoc.md'), pass its base name as fileName. Otherwise the API derives one from the markdown's first H1. Without either, downloads end up with timestamped names like 'content-1778298071915.docx' which is bad UX. 4. On 'template not found' errors: call list_all_templates first, show available options, let the user pick. Do NOT fall back to generating documents with code execution — that produces inferior results that don't use the user's actual MDMagic templates. 5. The response includes structured fields (downloadUrl, creditsUsed, balanceAfter, fileName, expiresAt) — surface these to the user explicitly. Don't paraphrase. The user wants to know exactly what they spent and what's left. 6. Page sizes: A3, A4, Executive, US_Legal, US_Letter. Default A4. Orientation: Portrait or Landscape, default Portrait. 7. CRITICAL — newlines in `content`: markdown is line-sensitive. Headings (#, ##), tables (| ... |), lists (-, 1.), and code fences (```) ONLY work when each starts on its own line. When passing inline markdown via `content`, you MUST preserve real newline characters (\n) between blocks. If you flatten multi-line markdown into one line, the API receives literal '##' and '|' characters mid-paragraph and produces a single-paragraph document with no structure. Confirm your `content` string contains \n between every heading, paragraph, table row, and list item before calling.
    ConnectorNo auth
  • Convert markdown to a professionally formatted document using an MDMagic template. IMPORTANT GUIDANCE: 1. Output format → what user gets: - 'docx' → a single Word .docx file - 'pdf' → a single .pdf file - 'html' → a single .html file - 'all' → a ZIP containing all three (DOCX + PDF + HTML) 2. If the user is ambiguous (e.g. 'convert this'), ASK which format they want before calling. Don't assume. 3. Filename: if the user attached a file (e.g. 'mydoc.md'), pass its base name as fileName. Otherwise the API derives one from the markdown's first H1. Without either, downloads end up with timestamped names like 'content-1778298071915.docx' which is bad UX. 4. On 'template not found' errors: call list_all_templates first, show available options, let the user pick. Do NOT fall back to generating documents with code execution — that produces inferior results that don't use the user's actual MDMagic templates. 5. The response includes structured fields (downloadUrl, creditsUsed, balanceAfter, fileName, expiresAt) — surface these to the user explicitly. Don't paraphrase. The user wants to know exactly what they spent and what's left. 6. Page sizes: A3, A4, Executive, US_Legal, US_Letter. Default A4. Orientation: Portrait or Landscape, default Portrait. 7. CRITICAL — newlines in `content`: markdown is line-sensitive. Headings (#, ##), tables (| ... |), lists (-, 1.), and code fences (```) ONLY work when each starts on its own line. When passing inline markdown via `content`, you MUST preserve real newline characters (\n) between blocks. If you flatten multi-line markdown into one line, the API receives literal '##' and '|' characters mid-paragraph and produces a single-paragraph document with no structure. Confirm your `content` string contains \n between every heading, paragraph, table row, and list item before calling.
    ConnectorNo auth
  • Creates a new Word (.docx) document at `path` with the given text content (and an optional title rendered as the heading). The path must be somewhere LMCP can write; Desktop/Documents/Downloads may need a one-time Files-and-Folders grant (System Settings → Privacy & Security → Files and Folders). Returns {created, path}. For a OneDrive or Google Drive path use onedrive_write_file / gdrive_write_file; to append to an existing doc use word_append, to read one word_read.
    Connector
    Destructive
    OAuth
  • Send a document for e-signature. Accepts PDF as base64, recipients, and field placement. Sandbox keys (sk_test_) send immediately (watermarked test mail). LIVE keys create a DRAFT and return it for human review unless confirm: true — nothing is emailed until confirmed. Field placement: page+x+y (percent, top-left origin) OR an anchor string, not both. After everyone signs, retrieve the sealed PDF with swiftsign_download_signed_pdf.
    Connector
    Destructive
    No auth
  • Attempt to download PDF of a CrossRef paper. Args: paper_id: CrossRef DOI (e.g., '10.1038/nature12373'). save_path: Directory to save the PDF (default: './downloads'). Returns: str: Message indicating that direct PDF download is not supported. Note: CrossRef is a citation database and doesn't provide direct PDF downloads. Use the DOI to access the paper through the publisher's website.
    ConnectorNo auth
  • Convert a PDF into structured content (tables, charts, formulas, headings, body text) using a two-stage pipeline (layout detection, then a vision-language model) rather than a single VLM call on the raw PDF -- calling a VLM on a raw PDF directly is a known-unreliable pattern for numeric tables. Measured accuracy (500-page real-world benchmark of government/corporate reports, ~51,000 table values checked): tables 95.2% digit-exact, body text 88.8%. This tool reads PDFs a VLM cannot read directly, including scanned pages and PDFs with corrupted/garbled text layers (common in older Japanese academic PDFs). For scanned Japanese documents the numbers hold up (99.4% on the same benchmark). For scanned Arabic, body text does NOT: characters are dropped mid-sentence and quantities can turn into different quantities, so body blocks from scanned Arabic are always flagged confidence:"estimated" -- tables in the same documents stayed exact in our measurement. Strong on Japanese-language documents specifically; the accuracy figures above were measured on Japanese material and are not a claim about every language. Chart values are extracted but are best-effort estimates (about 52% exact match, excluding axis tick labels) and are always flagged confidence:"estimated" in the result -- do not treat estimated chart numbers as authoritative. This is a PAID, ASYNCHRONOUS, per-page-billed operation: credits are reserved from the caller's PDFIntact balance before processing starts, and the response's _meta.credits_remaining shows the balance right after reservation. Processing takes real wall-clock time (roughly 7 seconds/page; a 500-page PDF takes about 42 minutes including a multi-minute cold start), so this tool returns a job_handle immediately without waiting -- call get_result with that job_handle to poll for completion instead of calling convert_pdf again. Always pass idempotency_key; reuse the exact same value if you retry the same request, otherwise retries can double-charge and double-process. Provide the PDF either as a public https URL (source.type="url", up to ~200MB) or inline base64 (source.type="base64", up to ~20MB) -- prefer the URL form for large files. Requires sign-in (OAuth): this session is not authenticated, so calling this tool will fail until the PDFIntact account is connected and authorized.
    ConnectorNo auth
  • List invoices/quotes/credit-notes with totals, status, line items, client and payments. These are sales documents; for recorded income entries use list_income, and for raw bank-feed lines use list_transactions.
    ConnectorOAuth
  • Read and edit the workspace pronunciation dictionary (Settings → Team → Pronunciation Dictionary). Use it whenever the user asks how a word, name or acronym is said. Do NOT respell the word in the voiceover script instead: the respelling shows in the script and captions, and every new video needs the fix again. An entry is WORKSPACE-WIDE: it changes the word in every video in this workspace; tell the user when you add or change one. It applies when speech is generated, so regenerate (voiceover_batch generate_speech) the clips that say the word. action: • list — entries for `language` ("" for all): {entries: [{word, spelling, ipa, language, case_sensitive}], count} • set — add or change `word`'s entry with exactly one of `spelling` (a sound-alike respelling, works on every voice; prefer it) or `ipa` (IPA phonemes, English ElevenLabs voices only, ignored on clips with [audio tags]). An existing entry is not overwritten: you get error "entry_exists" with `current`; show the user both, confirm, then call again with replace: true. • remove — delete `word`'s entry in `language` (exact spelling and casing) • to_ipa — convert `text` (e.g. a respelling) to IPA, to check an ipa entry before setting it Editing needs an editor or admin role and a plan with the dictionary; a refusal says which: tell the user, don't retry.
    Connector
    Destructive
    No auth
  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
    ConnectorNo auth
  • Upload ONE side of a postcard (front or back) as single-page PDF, PNG, or JPEG artwork. The file is stored VERBATIM — no page-size normalization and no reserved address zone — so you are responsible for the correct trim size plus bleed: 4x6 cards need 4.25"x6.25" artwork, 6x9 needs 6.25"x9.25", 6x11 needs 6.25"x11.25" (0.125" bleed on each edge). The selected delivery method prints the recipient address block over part of the BACK, so keep that area clear of critical content and review the quote's `design` block before payment. Returns a documentId with kind "postcard_art". Upload front and back separately, then quote with create_postcard_quote. Free; no payment required. Provide the artwork EXACTLY ONE way: `contentBase64` (base64-encoded pdf/png/jpeg) or `url` (publicly reachable). Text-based formats are rejected — postcards are artwork, not documents.
    ConnectorNo auth
  • Get a single metric with pre-reasoned signal interpretation, trend analysis (7d/30d/90d), confidence score with factor breakdown, momentum, and percentile ranking. Name the metric; list_metrics lists them and searches them by word. Needs a PreReason account: a signed in connection or an API key. Returns analyzed context (signal, trend direction, momentum, percentile among every stored daily close), not raw values. The signal is bullish, bearish or neutral on crypto series, and above-trend, below-trend or at-trend on every other metric, where the value sits against its trend, so a high yield reads above-trend. Use it to read where a metric stands against its trend and its own history, not just its number; for a reasoned view across several series, use get_context with a briefing. Every plan reads each metric's latest reading. Pro and above read every metric in full; on other plans, a metric outside the plan returns its latest reading only.
    ConnectorNo auth
  • Download a PDF from a URL and extract all text content, page by page. Use this to read the full text of a specific document — for example, an annual report PDF linked from a search_filings result. Best combined with search_filings: use search_filings to locate the document, then parse_pdf_to_text for the full text. Do not use for PDFs that are already well-represented in the database — search_filings is faster and returns pre-ranked, relevant excerpts. Not suitable for scanned (image-only) PDFs without embedded text; those pages will be returned as "(no extractable text)". Args: pdf_url: Direct HTTPS URL to the PDF file, e.g. https://example.com/report.pdf. Must be publicly accessible; authentication-protected URLs will fail. Returns: All text from the PDF with "--- Page N ---" separators between pages. Returns an error string if the download fails, the URL does not point to a valid PDF, or the document exceeds the 60-second download timeout.
    ConnectorNo auth
  • Upload ONE side of a postcard (front or back) as single-page PDF, PNG, or JPEG artwork. The file is stored VERBATIM — no page-size normalization and no reserved address zone — so you are responsible for the correct trim size plus bleed: 4x6 cards need 4.25"x6.25" artwork, 6x9 needs 6.25"x9.25", 6x11 needs 6.25"x11.25" (0.125" bleed on each edge). The selected delivery method prints the recipient address block over part of the BACK, so keep that area clear of critical content and review the quote's `design` block before payment. Returns a documentId with kind "postcard_art". Upload front and back separately, then quote with create_postcard_quote. Free; no payment required. Provide the artwork EXACTLY ONE way: `contentBase64` (base64-encoded pdf/png/jpeg) or `url` (publicly reachable). Text-based formats are rejected — postcards are artwork, not documents.
    ConnectorNo auth
  • 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. Читает и файлы, а не только страницы: PDF (включая сканы - распознаём текст), Word (docx), Excel (xlsx), PowerPoint (pptx), OpenDocument (odt/ods/odp/odg), RTF, EPUB и текстовые (txt/md/csv/json/xml). Адрес документа передавайте как есть: https://site.ru/otchet.docx. Старые двоичные .doc/.xls/.ppt не читаются - их отдаёт только LibreOffice, у нас его нет; нужен файл в новом формате. Цена: 1 кредит, самый дешёвый способ получить содержимое страницы (fetch_page - 3).
    ConnectorNo auth