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466,647 tools. Updated 2026-08-19 18:57

"Understanding File Systems and Their Functions" matching MCP tools:

  • Run a read-only SQL SELECT against the measurement tables openaq_get_measurements staged on a DataCanvas. Reference tables by the name the measurements call returned (measurements_<sensorId>). For aggregation (monthly means, exceedance counts) and cross-sensor comparison over series too large to inline. Only SELECT is allowed — writes, DDL, and file/network table functions are rejected.
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  • Run a single-statement SELECT against the canvas dataframes registered by bls_get_series. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied at the bridge layer — use bls_dataframe_describe to list available dataframes. Supports JOINs, aggregates, window functions, and CTEs. Optional register_as persists the result as a new dataframe with a fresh TTL for chained analysis. Canvas SQL operations consume zero BLS API quota. Requires CANVAS_PROVIDER_TYPE=duckdb.
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  • Display an interactive PDF upload widget directly in the chat. Use this when the user wants to upload a local PDF file from their device. This is the standard upload method for MCP clients (e.g. Claude) where file attachments with download URLs are not available. Do NOT call upload_pdf when using this tool — the widget handles the upload automatically. The widget renders inline and the PDF viewer appears after the user selects a file. Do NOT call view_pdf after this tool; the widget manages the UI. Never tell the user the file is still uploading; the widget handles the spinner. After the user uploads via the widget and notifies you, call check_upload_status(session_id=<session_id>) to discover the uploaded file and its job_id before proceeding with any operation.
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  • Diff two design systems from live URLs — the only URL-scoped design-token diff engine. Fetches both URLs in parallel, extracts their :root custom properties, and produces a structured diff across 8 dimensions: tokens added (in A not B), removed (in B not A), renamed (heuristic Levenshtein ≤ 2), value-changed (same name, different value), scale-stop-changed (spacing/radius/color scale steps), contrast-drift-per-pair (WCAG contrast ratio change for shared color tokens), structure-delta (token count + category distribution), and score-delta (runs /score on both URLs and diffs). Use this to answer "what actually changed between two design systems" or "how does our design system differ from a reference". When NOT to use: for single-site drift detection, use designesy_drift_score; for continuous monitoring, use designesy_monitor_score. Executable — fetches both URLs, extracts CSS + tokens, computes diff. No browser needed. Returns JSON: { ok, urlA, urlB, score (0-100, diff completeness), grade, pass, warn, fail, total, tokensA, tokensB, added[], removed[], renamed[], valueChanged[], scaleDiff, structureDelta, contrastDrift[], scoreDelta, checks[] }. Results cached ~24h per URL pair.
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  • Stage a Trial Balance spreadsheet (xlsx or csv, max 4 MB) for an entity by INLINING its bytes as base64. This path is ONLY for programmatic callers (a script, Claude Code, an automation) that already have the raw file on disk. If a HUMAN has the file — e.g. they attached it to this chat — do NOT use this tool and do NOT base64-encode the file: call create_upload_link instead and give them the link to upload it in their browser. File size does not change this: even a small attached file goes through create_upload_link — inlining a human-supplied file is unreliable and its bytes routinely truncate. Returns the upload session with detected columns and mapping SUGGESTIONS — nothing is ingested yet. Next: review the suggested column mapping with your user, then call confirm_column_mapping.
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  • Rank US-listed issuers by the change in their federal contract obligations between the two most recent comparable quarters. Use to find which public companies are gaining or losing federal business. Ranked by issuer rather than by recipient name, which requires rolling subsidiary entities up to a ticker. USAspending can rank recipient names but cannot tell you that Electric Boat and General Dynamics Land Systems are the same investable company. Large swings frequently reflect award timing rather than business trajectory, because a single multi-year obligation lands entirely in one quarter. Treat this as a list of things to investigate, not conclusions.
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  • Change an existing data spec's configuration. If no replacement file names are given, this runs synchronously (no upload needed): saves changes and — by default — re-runs AI analysis, returning the final status directly. If a replacement sample/format/target-schema file name IS given, this instead returns presigned upload URL(s); upload the file(s), then call finish_data_spec_update. Only pass the fields you want to change — omitted fields keep their current value.
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  • Save a Hermoso render — or ANY file — into the user’s connected Google Drive. Pass a Hermoso render URL as url (or urls[] for several); for a local/external file, call upload_file first and pass the url it returns. Optional folder (created if new) + name. Returns the Drive file(s) with a webViewLink. Needs Google Drive connected (Settings ▸ Connectors ▸ Google Drive — one connection covers Drive, Sheets and Docs). NOTE: Hermoso uses the drive.file scope, so it reaches ONLY the files it created plus any the user explicitly handed over with the Google file picker in the app — never their whole Drive.
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  • Run a read-only SQL SELECT against a DataCanvas table staged by an openFDA search tool (call one with stage=true; its response carries canvas_id + canvas_table). Enables GROUP BY, COUNT/SUM/AVG, time-series, and joins across the staged result set without re-paging the API. Call openfda_dataframe_describe first to get the exact table and column names. Results are capped at the canvas row limit — when truncated is true, page the rest with ORDER BY plus LIMIT/OFFSET. Scalar fields are stored as text (CAST for numeric math); nested objects/arrays are JSON columns — read them with DuckDB json functions, e.g. json_extract_string(openfda, '$.brand_name[0]'). Only SELECT is allowed — DDL, DML, COPY, and file-reading functions are blocked.
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  • Fetch geopolitical compute risk scenarios. Available: 'taiwan-strait' (4 TSMC disruption scenarios), 'iran-threat' (IRGC missile range vs Gulf compute), 'tokyo-earthquake' (Japan memory-fab exposure), 'south-china-sea' (submarine cable severing), 'abqaiq-2' (Saudi grid). Returns the scenario's summary plus its substrate serialized from the interactive page's own data modules — assumption scenarios / threat systems / affected assets with per-item sources and authority tiers, capped lists shipping their true totals. The propagation SIMULATION itself remains interactive-only at the returned URL.
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  • Run a single-statement SELECT against canvas dataframes registered by eia_query_route calls that passed stage: true — a query that staged nothing leaves no table to select from. Standard DuckDB SQL — joins, aggregates, window functions, CTEs all supported. Reference dataframes by the df_<id> handles returned by eia_query_route or listed by eia_dataframe_describe. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied. EIA data values are VARCHAR — use CAST(col AS DOUBLE) for arithmetic and aggregation. Optional register_as chains results as a new dataframe with a fresh expiry. Every dataframe named in the statement has its expiry extended by the query.
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  • Run a single-statement SELECT against the canvas tables staged by faostat_query_observations and faostat_commodity_profile (table names look like faostat_xxxxxxxx). Use this for cross-country and cross-item aggregation, GROUP BY rankings, joins, and time-series analysis over the full result set the inline preview only sampled. Standard DuckDB SQL — joins, aggregates, window functions, CTEs all work. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected; system catalogs (information_schema, sqlite_master, duckdb_*) are denied — list staged tables via faostat_dataframe_describe. Every row carries its data-quality `flag` — commonly A=Official, B=time-series break, E=Estimated, I=Imputed, M=Missing (value cannot exist), T=Unofficial, X=from an international organization, plus others FAOSTAT defines per domain — keep it in projections, treat any unrecognized flag as informational, and never assume it is official.
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  • Import the user's trace file (GPX, TCX, IGC, SBP or FIT, max 8 MiB) into THEIR SportsTrackLive account permanently — full analysis, 3D replay, appears in their profile with their default privacy setting. REQUIRES the user to be connected via OAuth (this MCP server supports it; the client starts the flow). For a user without an account, use create_ephemeral_replay instead. Provide the file exactly like analyze_activity_file (upload_id / file_url / file_base64).
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  • Show the user an inline upload card so they can hand you a file from their device (image/font/audio/…) — it lands in the project's hosted assets and the card gives you the hosted publicUrl. This is the path for any file the user has: an image they attached in this chat (attachments never reach MCP servers — you see them through vision only, so the user re-picks the same file here), a file on their machine, or a user-provided file you hold but can't upload yourself (over the 3 MB inline cap with no S3 egress — the card uploads from their browser, which is never egress-blocked). Returns a jobId — poll get_job_status; it stays running until they upload, then returns the publicUrl to reference in code. When you show the card, tell the user in a sentence why you're asking — e.g. that you can see their image but the file itself doesn't reach Floot, so re-adding it here is a one-click step — and ask them to say "uploaded" when done in case your polling ends before they finish. For files you hold yourself, use upload_asset; for AI-generated imagery, use generate_image.
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  • Canonical GlobalGov coverage numbers: total and open solicitation counts, countries covered, source systems, languages, vendor counts. Pre-computed nightly and served from cache; if the cache is cold the tool returns a retryable 'computing' error and the refresh is dispatched automatically. No arguments.
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  • Create a browser upload link for media files. ALWAYS use this when the user shares an image or video in chat — their file is local and cannot be passed directly to publish_content. WORKFLOW: 1. Call this tool to get an uploadUrl 2. Give the user the link to open in their browser and upload their file 3. After upload, call get_upload_session to get the public media URL(s) 4. Use the returned URL with publish_content or schedule_content Supports up to 20 files per session. Expires in 15 minutes.
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  • Generate a perceptually smooth gradient between 2-5 archive anchor colours. Each interpolated stop snaps to the nearest real archive colour by CIEDE2000. Anchor stops are kept true to their source. Choose linear (physically accurate Lab interpolation) or chroma_preserved (LCh interpolation, short-arc hue, avoids desaturated midpoints). Returns stop array, CSS linear-gradient string, or SVG swatch bar. Use for design briefs, colour journey visualisations, and gradient systems.
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  • Run a read-only SQL SELECT against a DataCanvas table staged by fema_search_nfip. Enables aggregation, GROUP BY, SUM/COUNT, time-series, and filtered analysis over the full NFIP claims result without re-fetching from the API. Call fema_dataframe_describe first to get the exact table name and column names needed for valid SQL. Only SELECT statements are allowed — DDL, DML, COPY, and file-reading functions are blocked.
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  • Safely evaluate an arithmetic expression and return the exact result. Supports +, -, *, /, //, %, ** (power), parentheses, the constants pi and e, and the functions sqrt(), abs(), round(). Does not execute arbitrary code.
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  • Check if the current Warp account has a payment method on file. Call this if the user asks about their payment status, or before booking if you want to confirm they can book. Returns has_card and onboard_url if a card needs to be added.
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