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459,923 tools. Updated 2026-08-17 09:20

"Information about Microsoft Excel or Excel-related tools" matching MCP tools:

  • 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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  • Run a full portfolio backtest for a previously created strategy. strategy_id: returned by create_strategy save_to_dashboard: set true to publish this run to the user's Helvetic dashboard so they can open it and download a PDF/Excel/CSV from the result page. Default false keeps the run in-chat only (analysable by backtest_id) to avoid cluttering the dashboard with exploratory runs. When the user asks to save/see it on the dashboard, run with save_to_dashboard=true (or call the save_to_dashboard tool). accept_data_risks: the run is REFUSED when an asset's data is assessed unusable (tiny history, dense invalid prices, extreme stale runs) or cannot be fetched at all. Set true ONLY when the user explicitly accepts running on flawed data; the result then carries severe data warnings instead.
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  • Return the full self-verifying AUDIT BUNDLE for a stored result as JSON - the same artifact the result page's "Export Audit Bundle" download produces, delivered in chat. It lets an external auditor independently reproduce every figure: raw input series (with re-derived SHA-256 hashes), every assumption, every displayed metric and its formula, data provenance (flagging any caller-supplied data as NOT verified by Helvetic), integrity checks, warnings, and a content hash of the bundle itself. backtest_id: from run_backtest, run_quant_research, run_universe_research, run_custom_ohlcv, run_custom_signal, or analyze_track_record. Use this when a client needs audit-grade reproducibility evidence in the conversation; pair with generate_report for the branded PDF/Excel/CSV.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • Describe what you want done to a file in plain language — e.g. "translate this contract to German", "pull every table out of this PDF into Excel", "shrink this video to under 25MB", "convert this to PDF". The instruction is routed to the right job automatically; if the request is not supported yet you get an honest explanation of what is. Provide EITHER source_url OR base64_content, plus a filename with extension.
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  • 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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Matching MCP Servers

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    An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.
    MIT

Matching MCP Connectors

  • 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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  • Switch on a group of tools that is not in this session's roster — no reconnect, no config edit. The default roster is everything EXCEPT `ads`, because paid-campaign management across ten platforms is 238 tools and about two thirds of the total schema weight, and most sessions never build a campaign. CALL THIS THE MOMENT YOU NEED ONE: if the user asks to build, budget, target, report on or change a campaign on Meta, Google Ads, LinkedIn, Reddit, Microsoft, Pinterest, X, TikTok, Snapchat, ChatGPT Ads or Apple Search Ads, call enable_tools({groups:['ads']}) first and the tools appear. Groups: core, research, create, channels, ads, files, workspace — or 'all'. Free, instant, and it never turns anything off.
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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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  • Create a new data source from an inline base64-encoded file (CSV, TSV, JSON, Excel, TXT, PDF). The file goes through the same validation and preprocessing as a web upload. Returns the data_source_id you can pass to run_analysis as soon as preprocessing completes (poll get_data_source_schema for readiness or pass wait_seconds to block here).
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  • Render an LBO result into a professional Excel workbook (Summary + year-by-year Projection table + Inputs sheet). Returns a 15-minute presigned R2 download URL. SERVER-TRUST: the deal is re-derived in-Worker from the supplied `lbo_result.inputs_echo` (the math is pure + deterministic) and the workbook renders Valuein's recomputed figures — never the caller's claimed values. If the claimed figures disagree, the workbook is still produced but stamped with a visible correction banner and the response `verification.status` is 'corrected'. Pair with `compute_lbo` for a typical flow: agent calls `compute_lbo({ticker, ...})`, then passes the structured result straight to `generate_lbo_xlsx({ticker, lbo_result, ...})` to materialise a shareable file. Tier: pro+.
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  • Lists the calendars in the Mac's Calendar app (Calendar.app, local/iCloud). For Microsoft 365 calendars use the m365 calendar tools instead.
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  • Returns Fluentive's security, privacy, and compliance information. Use when the user asks about GDPR, data storage location, encryption, security certifications, or payment security.
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  • Generate a PDF or Excel document from HTML (document_content) or a URL (document_url). Exactly one of document_content / document_url is required. By default the document is HOSTED and the tool returns a { download_url } you can fetch — ideal for agents (no large binary in the response). Set hosted:false to get the raw document back as base64, or async:true to enqueue a job and poll docraptor_get_document_status. IMPORTANT: real documents consume account credits (billed). Set test:true to generate a FREE, watermarked document while developing. DocRaptor API: POST /docs.
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  • 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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  • Give it up to 20 invoice URLs (PDF or page images) and get back one table ready to post: number, date, seller, buyer, net / tax / gross, currency. Every row is checked in code — net + tax must equal gross — and the batch total is re-added independently, so a row the model misread is flagged with the exact difference instead of quietly landing in your books. Mixed currencies get no batch total on purpose: adding them together would be an accounting error. CSV is UTF-8 with BOM so Excel opens it right.
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  • Give it up to 20 invoice URLs (PDF or page images) and get back one table ready to post: number, date, seller, buyer, net / tax / gross, currency. Every row is checked in code — net + tax must equal gross — and the batch total is re-added independently, so a row the model misread is flagged with the exact difference instead of quietly landing in your books. Mixed currencies get no batch total on purpose: adding them together would be an accounting error. CSV is UTF-8 with BOM so Excel opens it right.
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  • Give it up to 20 invoice URLs (PDF or page images) and get back one table ready to post: number, date, seller, buyer, net / tax / gross, currency. Every row is checked in code — net + tax must equal gross — and the batch total is re-added independently, so a row the model misread is flagged with the exact difference instead of quietly landing in your books. Mixed currencies get no batch total on purpose: adding them together would be an accounting error. CSV is UTF-8 with BOM so Excel opens it right.
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  • Tidies a spreadsheet export: removes duplicate rows, trims whitespace (half-width and full-width — Chinese exports are full of  ), unifies the half-dozen ways a cell can say "empty" (NA / null / - / 无), drops empty rows and columns, and can split one column into several. Returns the cleaned CSV plus exactly what changed: rows in, rows out, duplicates removed, cells trimmed per column. It can also transpose rows/columns and unpivot a wide table into a long one. The row arithmetic is verified in code — if in − removed ≠ out, the response says so instead of handing back a table nobody can check. Use when a CSV came out of Excel or an export and needs cleaning before analysis.
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  • Get information about related addresses of an input address. Note: This only includes the the "special" connections 'First Funder', 'Signer', 'Previous Signer', 'Multisig Signer of', 'Previous Multisig Signer of', 'Deployed via', 'Deployed by', 'Deployed Contract', 'Created Contract', 'Created by'. To get related wallets, also check address counterparties. First funder exchange withdrawal address does usually NOT belong to the same entity as the address, only deposit addresses. Only information is that it has been funded by the exchange.
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