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676,375 tools. Updated 2026-10-19 11:37

"Tools and methods for analyzing Google Sheets data" matching MCP tools:

  • Get USER PROFILES of people who interacted with an Instagram post. Returns full user data (bio, followerCount, followingCount, etc.). RETURNS USER PROFILES: id, username, fullName, biography, followerCount, followingCount, isVerified, profilePicUrl. Use for analyzing WHO engaged with a post. NOT FOR COMMENT TEXT: To read the actual comment content (what people wrote), use getInstagramCommentsByPostId instead. INTERACTION TYPES: "commenters" (users who commented), "likers" (users who liked). WHEN TO USE THIS TOOL: Analyzing commenters/likers demographics, finding influencers who engaged, building audience profiles, network analysis of who interacts with posts. WHEN TO USE getInstagramCommentsByPostId: Reading comment text, sentiment analysis of what was said, analyzing discussion content. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for commenters when stale. PAGING (responseType="paging"): Async paginated results (1000 users per page with default fields), returns operationId - IMMEDIATELY call checkOperationStatus to get results. CSV export included via dataDumpExportOperationId. Supports pageNumber/tableName for subsequent pages. Optional fields (default: ["id", "username", "fullName"]). Available: biography, isPrivate, isVerified, followerCount, followingCount, mediaCount, profilePicUrl. This is a safe, read-only tool for analyzing searchable information.
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  • Low-level Telegram API (MTProto) invoke for methods not wrapped by other tools. Dangerous methods require allow_dangerous=true. Success: API result dict or normalized error. PII and credential-shaped fields (phone, access_hash) are dropped from a successful result by default; pass include_sensitive=true for the raw payload. A bare message id needs a chat binding: requests with no peer field (messages.GetMessages, messages.DeleteMessages) are refused, because a bare id resolves against an arbitrary dialog. Use channels.GetMessages or messages.GetHistory, which carry the binding. messages.GetHistory cannot address a forum topic (no thread_id/top_msg_id in the schema, and channels.GetHistory does not exist) -- use messages.Search with top_msg_id, or the high-level get_messages with reply_to_id. Full documentation: https://github.com/leshchenko1979/fast-mcp-telegram/blob/main/docs/Tools-Reference.md
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  • Low-level Telegram API (MTProto) invoke for methods not wrapped by other tools. Dangerous methods require allow_dangerous=true. Success: API result dict or normalized error. PII and credential-shaped fields (phone, access_hash) are dropped from a successful result by default; pass include_sensitive=true for the raw payload. A bare message id needs a chat binding: requests with no peer field (messages.GetMessages, messages.DeleteMessages) are refused, because a bare id resolves against an arbitrary dialog. Use channels.GetMessages or messages.GetHistory, which carry the binding. messages.GetHistory cannot address a forum topic (no thread_id/top_msg_id in the schema, and channels.GetHistory does not exist) -- use messages.Search with top_msg_id, or the high-level get_messages with reply_to_id. Full documentation: https://github.com/leshchenko1979/fast-mcp-telegram/blob/main/docs/Tools-Reference.md
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  • Which export destinations this account has connected (Close, GoHighLevel, Google Sheets) and whether each is ready to receive leads. Check this BEFORE export_leads or create_automation with a CRM destination — those fail if the integration isn't connected, and Close additionally needs one manual export first to save its field mapping. File destinations (csv/xlsx/json) always work and need nothing connected.
    ConnectorNo auth
  • Get a download link for every response to a form, as a spreadsheet (CSV, which opens directly in Excel, Numbers and Google Sheets) or as JSON. Use this when someone wants the whole dataset in their own hands — "send me the responses", "export this", "can I get a spreadsheet". Returns a link, not the data: a few thousand answers do not belong in a conversation. For questions you can answer here — counts, totals, which option is winning — use get_response_stats, and for reading particular answers use list_responses. The link works for one hour and needs no login, so treat it as sensitive and give it only to the person who asked. Example: { form_id: "…", format: "csv" }
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  • Get full details of a specific expense report including all expenses, totals, and compliance status. Use only when the user explicitly asks to inspect an existing report's details. Without checkFreshness:true, returns the stored report only. When explicitly requested together with analysisRequested:true, freshness reads canonical Google Sheets sources with a 5-second bound; if full tax-year replay is unavailable, status is unknown, not current. Never call this as a preflight or follow-up to creating, sharing, or billing from a report; those tools already return the requested result and links.
    ConnectorNo auth

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  • List the saved payment methods (used only to pay for flight bookings, not for cards or adding funds). Returns each method with its id, brand, last 4 digits, and expiry, and marks the default one. Use setup_payment_method to add a new one. The gated tools set_default_payment_method and remove_payment_method also exist; call them by name even though they aren't in the tools list.
    ConnectorNo auth
  • Discover AgentMarketplace's capabilities, tools, auth methods, and scopes. Call this first when connecting to AgentMarketplace to understand what's available and how to authenticate. No authentication required. Returns a catalog of available tools, resources, auth methods, and scopes.
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  • Read the text content of a Google Doc, Sheet, or Slides presentation. Docs export as plain text, Sheets as CSV, Slides as plain text. For large files, returns a size warning instead of content — use max_chars and offset to read in chunks. file_id also accepts a ShareWatch handoff code of the form SW-XXXXXXXX. The user gets one by opening a file from Google Drive with ShareWatch, and it stands for that file until it goes unused for 30 days. The result always reports the real file_id, so use that value for any follow-up call rather than the code.
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  • Publish a multi-scenario comparison into the signed-in user's Google Sheets — sim_compare's export, the counterpart of sim_publish for a single scenario. Runs every scenario on one shared seed (the same server-enforced sharing sim_compare uses, so differences are the scenarios and not the dice) and writes a comparison table plus a trajectory chart, rather than one scenario's own data tabs. Returns the sheet URL. Counts against the same daily publish quota as sim_publish, and costs 1 token per scenario from your account's compute bucket.
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  • List where your signals are delivered — Slack channels, webhooks, Google Sheets, n8n, Clay and Notion — with each destination’s health and recent failure state. Connection settings (URLs, tokens) are never returned.
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  • Browse the complete WORKMINE catalog for free: paid API names, exact USDC-denominated prices, HTTP methods and URLs. Use this when comparing available tools; use find_workmine_tool when you already have a natural-language task. This catalog call itself does not execute or purchase a paid API.
    ConnectorNo auth
  • Download one Drive file's raw bytes as base64 (binary-safe — images, PDFs, etc.). NOT for Google-native Docs/Sheets/Slides (no raw binary exists — use read_file_content with export_mime_type instead). Hard-capped at 5MB; larger files error rather than silently truncating. Needs the Drive CONTENT scope (drive.readonly). Pass `account` when more than one content-capable account is connected.
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  • Fetch detailed Google Maps information for a known `place_id`. Use google_map_search to find places or google_map_place_photos and google_map_place_reviews for the full photo and review data.
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  • Fetch detailed Google Maps information for a known `place_id`. Use google_map_search to find places or google_map_place_photos and google_map_place_reviews for the full photo and review data.
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  • Run a read-only query against one of this organisation's connected databases — PostgreSQL, MySQL, SQL Server, Redshift, Snowflake, Oracle, BigQuery or Google Sheets — in that connection's own SQL dialect, and return rows. One SELECT, WITH, EXPLAIN or SHOW statement; a statement that could change data is refused. It returns at most 500 rows and about 100 KB: a larger result comes back cut, with truncated: true and totalRows, so prefer a LIMIT or an aggregate. Where a question involves a business number (revenue, churn, active users…), fastero_get_definitions holds this organisation's own expression for it.
    ConnectorAPI key
  • Get Reddit subreddit by name with its posts. FAST (default, omit responseType or responseType="fast"): Returns subreddit data with up to 300 posts directly (use limit param to reduce). Auto API fallback for fresh data. PAGING (responseType="paging"): Async paginated results (100 posts per page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. RESPONSE STRUCTURE: Returns { results: { subreddit: {...}, posts: [...] }, pagination: {...} }. FIELD SELECTION: Use subredditFields for subreddit data optimization, postFields for post data optimization. First searches database for both subreddit and posts, then external API if data is stale or missing. This is a safe, read-only tool for analyzing searchable information.
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  • Find outliers and anomalies in structured data — ideal as a second step after pulling records from Google Sheets, Airtable, Supabase, Notion databases, HubSpot, Financial APIs, GitHub, NPM, or any source that returns rows of JSON. Fully stateless: send known-good rows as training and suspect rows as test in ONE call. Returns per-row anomaly scores, confidence levels, and the top features explaining WHY each row was flagged. Typical workflow: (1) Pull data from another tool (e.g. Google Sheets, Supabase query, HubSpot deals). (2) Pass the first N rows as training (normal baseline). (3) Pass remaining or new rows as test. (4) Report which rows are anomalous and why. Works on JSON objects, numbers, text, arrays. No separate training step required. Examples: - Spreadsheet QA: Pull 500 sales rows from Sheets → train on first 400 → test last 100 → flag outlier entries - Financial screening: Get ratios for 50 stocks from a financial API → find anomalous ones - CRM hygiene: Pull HubSpot deals → flag deals with unusual discount/value patterns - Dependency audit: Get NPM package metrics → flag packages with anomalous quality scores - Commit review: Pull GitHub commit metadata → flag unusual commit patterns
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  • Find outliers and anomalies in structured data — ideal as a second step after pulling records from Google Sheets, Airtable, Supabase, Notion databases, HubSpot, Financial APIs, GitHub, NPM, or any source that returns rows of JSON. Fully stateless: send known-good rows as training and suspect rows as test in ONE call. Returns per-row anomaly scores, confidence levels, and the top features explaining WHY each row was flagged. Typical workflow: (1) Pull data from another tool (e.g. Google Sheets, Supabase query, HubSpot deals). (2) Pass the first N rows as training (normal baseline). (3) Pass remaining or new rows as test. (4) Report which rows are anomalous and why. Works on JSON objects, numbers, text, arrays. No separate training step required. Examples: - Spreadsheet QA: Pull 500 sales rows from Sheets → train on first 400 → test last 100 → flag outlier entries - Financial screening: Get ratios for 50 stocks from a financial API → find anomalous ones - CRM hygiene: Pull HubSpot deals → flag deals with unusual discount/value patterns - Dependency audit: Get NPM package metrics → flag packages with anomalous quality scores - Commit review: Pull GitHub commit metadata → flag unusual commit patterns
    ConnectorNo auth