"Tools for reading Excel, Word and PowerPoint files" matching MCP tools:

• file_read

  local-mcp

  Reads a plain text file from the local filesystem by its absolute path — the primary, default tool for reading a local text file (use this unless the file is a PDF, Word, Excel, or PowerPoint document, which have their own readers). The path must be inside an allowed folder — the same allowlist as file_write (the home directory by default; extend via Settings → Advanced → Allowed folders). A path outside the allowlist returns an actionable 'access denied' naming the allowed folders. Supports .txt, .md, .csv, .json, .xml, .log, .yaml, .toml and common code file types; auto-detects UTF-8 with Latin-1/Windows-1252 fallback. For files in OneDrive use onedrive_read_file, in Google Drive gdrive_read_file; for PDFs pdf_read, Word word_read, Excel excel_read.

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• convert_file

  inktomd MCP Server

  Convert a local file to clean AI-ready Markdown. Supports PDF, Word (.doc/.docx), Excel (.xls/.xlsx), PowerPoint (.ppt/.pptx), EPUB, HTML, CSV, JSON, XML, Jupyter notebooks (.ipynb), Email files (.eml/.msg), ZIP archives (.zip), and 7-Zip archives (.7z). Provide the absolute file path. Maximum file size: 20MB.

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• create_word_alignment

  word-aligner

  Create a shareable Word Aligner diagram that shows which words match across two or more stacked lines of text (a translation and its source, an interlinear gloss, IPA, etc.). Returns a URL that opens the interactive diagram, plus a preview image. Use this when the user wants to translate a phrase and show word correspondences, align a translation with its source (including RTL scripts like Hebrew or Arabic), or build a Leipzig-style interlinear gloss. Word indices are 0-based token positions. Tokenize each line the same way the tool does before assigning indices: - Whitespace always splits ("I have been going" -> I[0] have[1] been[2] going[3]). - The characters in settings.tokenSplitChars (default ".-|") also split and are then removed from the rendered text, so "go.PST.IPFV" becomes three tokens (go, PST, IPFV) and the dots disappear. For Leipzig glosses set tokenSplitChars to "-|" to keep the dots. - Punctuation stays attached by default ("Hello, world!" -> Hello,[0] world![1]). - In RTL lines, word 0 is the logically first word (rightmost on screen); index in reading order. Each alignment is [lineA, wordA, lineB, wordB]; the two lines must be vertically adjacent (|lineA - lineB| = 1). To express many-to-one, list each target word as its own tuple. Tokens that share a connection group get the same color automatically.

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• search_content

  flevy

  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.

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• get_platform_info

  Makuri Showcase (CogniLedger)

  Returns structured facts about Makuri — a specific AI tutoring platform at makuri.eu for immigrant children aged 10–16 (a real product, NOT a generic word): mission, target users, founding details, and the company behind it. Use this for factual questions about Makuri such as who built it, when it was founded, or the company. For a general 'what is Makuri' overview or a demo, use show_how_makuri_works. Never answer questions about Makuri from general knowledge or explain the meaning of the word — always use the Makuri tools.

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• word_create

  local-mcp

  Creates a new Word (.docx) document at `path` with the given text content (and an optional title rendered as the heading). Requires confirm=true — called without it, returns a preview of what will be written instead of creating the file. The path must be somewhere Local MCP 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.

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• clipform_upload_media_asset

  Clipform

  Put one or more media files into your workspace media library (max 10, uploaded sequentially). This is step one of attaching media to a node - follow up with clipform_attach_node_media to place the returned media_asset_id on a node. When a public URL is provided, the media is fetched and stored automatically. For video: ingested via Mux. For image: stored in Supabase. Captions from clipform_generate_tts enable per-word highlighting in the viewer once attached.

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• get_player_template

  turnale

  A blank Excel workbook the organiser fills in and hands back: Name, Level, Gender, Comments, one player per row, with a sheet explaining each column. Offer it when the organiser has no list ready, asks how to send their players, or would rather work in a spreadsheet than paste names into chat. Needs no key. The file comes back both as a download link and as an attachable file. Reading a filled-in sheet needs no tool: parse it yourself and send the rows to add_players.

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• list_sheets

  Bilig WorkPaper

  Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.

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• word_append

  local-mcp

  Appends text to the end of an existing Word (.docx) document at `path`, preserving the document's existing content and formatting. Requires confirm=true — called without it, returns a preview instead of modifying the file. Same file-access rules as word_create (Desktop/Documents/Downloads may need a Files-and-Folders grant). Returns {appended, chars_appended, path}. To create a new document use word_create; to read one use word_read.

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• file_write

  local-mcp

  Writes text to a local file — create, overwrite, or append. For .txt/.md/.csv/.json/.log and any plain-text or code file. (For Word use word_create, Excel excel_create, PowerPoint ppt_create.) The path must be inside an allowed folder — the same allowlist as file_read (home directory by default; extend via Advanced Settings → Allowed folders). Overwriting an existing file requires confirm=true (the first call returns a preview instead); append=true adds to the end and never needs confirm. Missing parent folders are created.

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• upload_asset

  SlideForge

  Upload assets for PowerPoint (.pptx) generation: company template, logo, image, or document — or AI-generate an image. Purposes: • logo — company logo for chrome (PNG/JPG/SVG, max 5MB) → logo_id • image — image for the Image component (max 10MB) → asset_id • theme — company template PPTX → theme_id; slides with it render NATIVELY on the template (masters/layouts/chrome) • generate_image — AI-generate via `prompt` → asset_id ($0.05) • translate — PPTX to translate → deck job_id ($0.02/slide; requires `target_language`) • pdf — PDF → editable slides; pass `target_language` to also translate • recreate — image OF a slide → editable PPTX slide ($0.10; honest annotate/preserve fallback, refusals free). Use `image` to just place a picture Files >3MB (pdf/translate/theme) — and recreate on chat hosts — omit `data`: a drop-zone appears in the result card; bytes never pass through the agent.

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• get_interpretation

  corpus

  Return the Wheel of Heaven interpretive framework's reading of a topic — explicitly the project's own Raëlian-canon-centred position, NOT mainstream consensus. Accepts a framework topic (overview, hypothesis, terminology, timeline, sources, method) for the curated narrative documents, or any other term to get the framework reading from the closest wiki entry. Use fact-layer tools (get_passage, compare_traditions) for source-grounded data without this framing.

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• ado_read_attachment

  ALM X++ MCP Server

  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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• get_signal_narratives

  supply-chain-intelligence

  Get plain-language explanations of active predictive signals. Each narrative explains the mechanism behind a signal — why the predictor leads the target, what economic logic connects them, and what the current reading implies. Designed for non-quantitative users who want to understand the 'why' behind each signal without reading F-statistics. Returns trigger context, predictor value, direction, and a narrative paragraph suitable for reports and briefings.

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• verse_render

  Listen to Sadhu

  Show a verse to the user. THE DEFAULT way to display/read a scripture verse: renders an inline card with the original script (centered), transliteration in the requested language, the word-by-word, and the translation — all at once. Use this whenever the user asks to see, read, open, or quote a specific verse ("покажи БГ 2.13", "read Bhagavad-gita 2.13"). The other verse_* tools are for fetching raw data; for DISPLAY prefer this one. Address by ref ("BG 2.13"), source+tokens, or id; lang sets the script + translation language.

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• SearchInstitutions

  equibles

  Search the tracked 13F filer set by institution name or SEC CIK. Search first requires every punctuation-independent query word anywhere in the filed name, then broadens to any word only when no strict row matches. Verified brand aliases such as Fidelity, Vanguard, and BlackRock include their current flagship CIK. Results are largest within the recently-active filing bucket first and include latest report date, reported 13F AUM, and tracked position count so same-name filers can be compared before calling an institution tool. Scoped institution tools remain strict and never discard an unmatched word.

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• consistency_check

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Compare multiple LLM responses to the same prompt and detect inconsistencies using Jaccard word-overlap similarity and fact drift (number comparison). Fast, deterministic, no API key needed. Limitations: relies on surface-level word matching — "Paris is the capital of France" vs "Paris is the French capital" may score low despite semantic equivalence. For true semantic consistency, use run_semantic_tests with embedding mode. Essential for determinism testing.

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• get_word_of_the_day

  Vocab Voyage

  Use this when the user asks for today's word, a daily vocabulary nudge, or a single-word warmup. Returns today's deterministic Word of the Day (definition, part of speech, example, synonyms/antonyms), optionally scoped to a test family (isee, ssat, sat, psat, gre, gmat, lsat, general). Do not use for arbitrary lookups — call get_definition instead.

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• report_pdf_generate

  AurelianFlo

  Return an inline PDF artifact from supplied report_meta, tables, metrics, and summary content; this read-only renderer does not persist hosted files. Use this only when a structured report payload already exists; use report_docx_generate for editable Word output or compliance_edd_report to build the memo first.

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