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700,359 tools. Updated 2026-10-25 01:20

"A tool for working with spreadsheets and data analysis" matching MCP tools:

  • Collapsed As-Built / But-For analysis on a post-impact XER. Implements AACE RP 29R-03 §3.8 Modeled / Subtractive / Single Base method (paired with MIP 3.3 Windows for the dual-method gap report per SCL §11.5). Validates a forensic windows analysis (MIP 3.3) by independently computing the same project drift via subtractive removal of delays from the as-built schedule. For each delay event, the as-built duration of every ``affected_activity`` is shortened by ``impact_days`` working days on that activity's calendar (or removed entirely if ``removal_method="remove"``), then CPM re-runs and the resulting "but-for" finish date is compared to the as-built finish. Cumulative pass removes ALL events at once for a project-level but-for finish. Every finish shift is stated in working days on ``workday_calendar``; the calendar-day span of the same shift is kept beside it, and ``day_unit_basis`` names the unit of every bare ``*_days`` key in the result. Use this tool when opposing counsel demands a but-for analysis or you need a dual-method validation pairing §3.3 (windows) with §3.8 (collapsed-as-built). For prospective fragnet insertion (MIP 3.7), use ``time_impact_analysis_fragnet`` instead. Args: as_built_xer_path: server-side post-impact XER (after delays incurred). as_built_xer_content: full text of post-impact XER (alternative for hosted/remote use). Supply EXACTLY ONE of path/content. delay_events: list of event dicts. Each must have ``event_id``, ``affected_activities`` (list of task_codes), and ``impact_days`` (number of working days on the affected activity's calendar). Optional: ``removal_method`` ('shorten'|'remove'), ``responsible_party``, ``name``, ``description``. output_dir: optional output dir for HTML/CSV (tempdir if ""). project_name: optional override. removal_method: global default 'shorten' or 'remove'. contractor_filter: when True, exclude contractor-caused events from the cumulative pass (owner audit mode). Returns: { "as_built_finish": "YYYY-MM-DD", "per_event_results": [{event_id, but_for_finish, impact_workdays_collapsed, collapse_state, duration_removal_basis, finish_driver_after_removal, ...}, ...], # impact_workdays_collapsed is the event's finish shift in # working days on workday_calendar. Each event also carries # impact_days_collapsed: the same shift in calendar days. # duration_removal_basis discloses WHAT duration was removed # and on what basis; finish_driver_after_removal discloses # WHAT drives the but-for finish (incl. whether it is bound by # the data-date floor) so a reader sees WHY the finish did or # did not move across data dates. "cumulative_but_for_finish": "YYYY-MM-DD", "cumulative_impact_workdays": int, # working days on workday_calendar "cumulative_impact_days": int, # the same shift in calendar days "cumulative_collapse_state": str, # a 'locked_by_actuals' zero is not "no impact" "workday_calendar": str, # the calendar every working-day figure is stated on "day_unit_basis": dict, # each bare *_days key: 'working_days' or 'calendar_days' "dual_method_gap": dict | None, # working days only "output_files": {...}, "warnings": [...], "method": "AACE 29R-03 §3.8 (Modeled/Subtractive/Single Simulation)" }
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  • Aggregate all quant tools into one JSON stock analysis. The tool reuses the existing MCP tools as its data sources, then derives a direction signal, direction score, bullish factors, bearish factors and plain-English summary. If one underlying tool is gated, unavailable or raises an error, the remaining tools still contribute to the final result (status "partial"); if every underlying tool fails, the whole call fails (status "error", isError=True) instead of a misleadingly "successful" empty analysis. Args: symbol: Stock symbol, e.g. "NVDA". refresh: Request fresh IV Radar data instead of using the backend's fresh IV cache. Defaults to False. lang: Language for `summary`, `bullish_factors` and `bearish_factors` - "en" (default), "zh" or "ja"; regional forms like "zh-CN" are accepted. Everything else in the response, `signal` included, is language-independent, so an existing caller that omits this gets byte-identical output to before.
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  • Aggregate all quant tools into one JSON stock analysis. The tool reuses the existing MCP tools as its data sources, then derives a direction signal, direction score, bullish factors, bearish factors and plain-English summary. If one underlying tool is gated, unavailable or raises an error, the remaining tools still contribute to the final result (status "partial"); if every underlying tool fails, the whole call fails (status "error", isError=True) instead of a misleadingly "successful" empty analysis. Args: symbol: Stock symbol, e.g. "NVDA". refresh: Request fresh IV Radar data instead of using the backend's fresh IV cache. Defaults to False. lang: Language for `summary`, `bullish_factors` and `bearish_factors` - "en" (default), "zh" or "ja"; regional forms like "zh-CN" are accepted. Everything else in the response, `signal` included, is language-independent, so an existing caller that omits this gets byte-identical output to before.
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  • Calculation, not advice. Verify with a professional before acting. Standard amortizing loan calculator. Pick this for a single fixed-rate installment loan (mortgage, auto, student, personal) with one amortization schedule; pick `calculate_cc_payoff` for a credit card, which carries revolving balances, multiple APR segments, and a snowball or avalanche strategy this tool does not model. Returns: - monthly payment, total interest, and a payoff date (null when the loan does not clear within its term) - a bucketed Analysis suitable for chart rendering. The Analysis includes KPIs, annotations (e.g. crossover month), and summary strings When extra_monthly_payment is supplied, every computed figure in the response outside with_extra describes this loan without the extra payment, including monthly_payment, payoff_months, total_paid, total_interest, remaining_balance_at_term, payoff_date, months_to_halfway_principal, months_to_interest_flip, and every value under analysis; a warnings[] entry names this. The response includes `chart_hints` with rendering directives any client can use. This tool does not support output: 'inline' on any transport.
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  • List the documents stored with a database (uploaded via create_upload_link), newest first: id, filename, size, the name they are attached to, and markdownChars - the size of the Markdown copy read_document returns (null when there is none, with markdownNote saying why). Pass nameId for one name's documents. Read-only. Use it to find a document's id before read_document, or to see what source files (PDFs, spreadsheets, notes) back a database. Data files loaded by import_file are not documents and are not listed here. Returns {database, count, documents}, every document at once (no paging). Errors database_not_found when the database does not exist or this user cannot open it.
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  • Initializes a Blockscout MCP session: returns server reference data, the `blockscout-analysis` skill pointer, and the URI resolution rule. Call this tool exactly once per session, before any other tool, and reuse its payload for the rest of the session; do not call it again.
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    Provides comprehensive control over Google Sheets to read, write, format, and manage spreadsheets directly through natural language. It includes extensive tools for data manipulation, conditional formatting, and cell protection, along with integrated PostgreSQL database query capabilities.
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Matching MCP Connectors

  • Paid MCP server for EAN, UPC, and GTIN validation, normalization, correction, and batch analysis.

  • NCUA call report data for US credit unions, 2018-2026: profiles, peer comparison, time series.

  • Get comprehensive transaction information. Unlike standard eth_getTransactionByHash, this tool returns enriched data including decoded input parameters, detailed token transfers with token metadata, transaction fee breakdown (priority fees, burnt fees) and categorized transaction types. By default, the raw transaction input is omitted if a decoded version is available to save context; request it with `include_raw_input=True` only when you truly need the raw hex data. Essential for transaction analysis, debugging smart contract interactions, tracking DeFi operations.
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  • Initializes a Blockscout MCP session: returns server reference data, the `blockscout-analysis` skill pointer, and the URI resolution rule. Call this tool exactly once per session, before any other tool, and reuse its payload for the rest of the session; do not call it again.
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  • Get comprehensive transaction information. Unlike standard eth_getTransactionByHash, this tool returns enriched data including decoded input parameters, detailed token transfers with token metadata, transaction fee breakdown (priority fees, burnt fees) and categorized transaction types. By default, the raw transaction input is omitted if a decoded version is available to save context; request it with `include_raw_input=True` only when you truly need the raw hex data. Essential for transaction analysis, debugging smart contract interactions, tracking DeFi operations.
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  • Lists all automation-enabled Data Templates (Forms) available for the current group. Use this tool first when you need to determine which Data Template (Form) should be used for a user's request, before retrieving its schema or working with submissions.
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  • WRITE tool — generates a fresh AI review analysis for a tracked app from its recent reviews (praise/complaint themes, sentiment, feature requests, trend vs the previous run). At most one analysis per app+country every 90 days (429 with the next available time while in cooldown — use sonar_review_insights to read the current one); needs at least 5 recent reviews. Requires a paid (non-trial) Indie plan and an authorized Sonar account or an API key with the write scope.
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  • Extract a seller's full product catalog: every ASIN they sell with brand, category, price, Prime status, variant counts, and rating data. Also returns dynamic refinement filters (department, shipping, sustainability) for drilling into the catalog. Use this tool for competitor inventory analysis, stock monitoring, and pricing-strategy research. If you need the seller's legal identity or reputation instead of their products, use get_seller_profile. Each page costs 1 credit. Start with one page and use sort_by (e.g. 'exact-aware-popularity-rank' for best sellers first) to surface the most relevant products early. Provide EITHER seller_id OR url — never both.
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  • Filter the how-to index by analysis family, tool, vertical, and/or a case-insensitive text query against title, analysis name, intro, problem statement, and step operations (with practitioner-synonym coverage, e.g. attrition/turnover/churn, logistic regression/classifier, power bi/dax, diversity/simpson/blau). All filters are optional and combine with AND; call with no arguments to get every page (same as list_howto_pages).
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  • Create a public share link for one object. Anyone with the link can download the file without a quickS3 account until the link expires. Use this tool only when the user asks to share a file with someone. To download a file yourself, use create_download_link. This tool needs Read and Share on the file. The link stops working if this access grant is revoked or expires. It also stops working if Read or Share on the file is removed, or if the organisation turns share links off.
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  • Check whether Analysis-Ready Cloud-Optimized (ARCO) data is available for a dataset. For analysis tasks, call this (and check for a "Kerchunk Reference Files" group via get_file_groups) before reaching for raw data files — reading through ARCO/kerchunk references avoids downloading whole files just to subset them. When picking among kerchunk reference variants, always use the one with "-osdf" in its name (see get_arco_variables) — other variants' chunk targets can be internal paths that only resolve on NCAR's network. Open it with xr.open_dataset(url, engine="kerchunk", storage_options={"remote_protocol": "https", "lazy": True}) rather than hand-building an fsspec reference filesystem. Args: dsid: Dataset ID (dNNNNNN), e.g. d083002
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  • Use this when you need to know whether a 2024-2028 UK date is a Monday-Friday working day after applying the official bank holidays for the selected division. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery. Do not use this when you need a local council, school, employer, financial-market, emergency-closure or non-UK calendar, or a date outside 2024-2028. What it computes: Checks whether a date is a normal working day in England and Wales, Scotland or Northern Ireland using a pinned snapshot of the official GOV.UK bank-holiday feed. Example user requests: Is 28 December 2026 a working day in England and Wales, or the Boxing Day substitute holiday? | Is Scotland working on 15 June 2026? | Check whether 13 July 2026 is a working day in Northern Ireland. Inputs: date (date); division (enum, optional). Complete JSON argument examples: {"date":"2026-12-28","division":"england-and-wales"} | {"date":"2026-06-15","division":"scotland"} Outputs: date, weekday, division, division_name, is_working_day, day_type, bank_holiday_name, bank_holiday_notes, status_basis, source_url, licence, dataset_version, coverage_start, coverage_end, source_snapshot_sha256. Formula: official bank-holiday event → non-working; else Saturday/Sunday → non-working; else Monday-Friday → working Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/uk-working-day with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/everyday/uk-working-day.md
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  • Read an uploaded file (PDF, Word, PowerPoint, spreadsheet, text) as markdown. Find file ids with workspace_folders_browse (a folder's items of kind workspace_file) or search_workspace. For anything long, call with `outline: true` first: it returns the headings with their character offsets and the total length. Then read only the sections you need with `offset` and `maxChars`. Spreadsheets come back as tables. A file that can't be read as text says so; don't guess at its contents.
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  • Delete a hosted page (a dashboard is deleted with fastero_delete_dashboard). Its link stops working for everyone in the project, answering that the page was not found, and its automatic refresh stops. The widgets it read, and their queries and spreadsheets, are kept. To change what it shows and keep its link, fastero_update_page replaces its HTML in place. Answers with the page’s _id.
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    Destructive
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  • Delete one heartbeat for good: its ping_url stops working (404) and no tool restores it. Use it only when the user asked for deletion; to stop alerts for a while use pause_heartbeat. Requires a key with the write scope. Returns {"success": true}.
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  • Checks the connection to the FalaAI API and returns its health and version (status, version, uptime, database, phase, launch date). Use it FIRST to confirm the MCP is working before any billable call. This tool is FREE: it does not consume credits, does not require the API key (the health endpoint is public), performs no analysis and stores nothing.
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  • Send a message to the Studio agent and wait (up to ~45s) for its answer. The agent builds on a working copy and answers with a PROPOSAL (apply it with apply_turn), a question, a priced plan (answer with plan_approved:true to build it), or a run request with its price. If the turn is still working when the wait ends, poll get_turn.
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