"Tools for finding trending keywords, ad costs, and storing data in Google Sheets" matching MCP tools:

• delete_ad_group

  Growomat

  Delete an ad group. By default the call fails with a 409 when the ad group still has dependent ads or keywords — pass cascade=true to delete them in the same request. Permanently deletes the resource. Irreversible. Scoped to the active Space — see set_active_space to switch, or pass space_id to override for this one call.

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• get_competitor_keywords

  RevenueScope: revenue-first analytics for your EC site

  Return the latest competitor SEO snapshot for the site (FD-041): which keywords each tracked competitor DOMAIN ranks for on Google (Japan/ja), at what position, with monthly search_volume, cpc and etv (estimated monthly traffic — a visit estimate, not a monetary value), plus how each rank moved vs the previous snapshot. READ-ONLY — this tool never runs a research (that costs money and is triggered separately from the dashboard, the competitor-research Edge Function); it only reads what was already fetched. The response is summary-first (token-aware): each domain carries a constant-size `summary` (total_keywords, total_etv, volume_bands and rank_bands histograms, and vs_previous new/lost/improved/declined/same counts) that always reflects the FULL keyword set, while `keywords` returns only the top rows ranked by `sort` (etv default | volume | rank; default limit 10 per domain, max 100) with a `truncated` block (shown/matching_total/lost_total). rank is a POSITION: smaller is better, so a NEGATIVE rank_delta means the competitor's ranking IMPROVED (change ∈ new/improved/declined/same/unknown). Keywords the competitor ranked for before but lost are disclosed in `lost_keywords` (top 10 by previous etv), never dropped silently. Pass `domain` to focus one competitor, `min_volume` to drop low-volume keywords. When the site has NO completed research yet the response is { researched:false } with a `guidance` string explaining a research must be triggered from the dashboard first — this tool cannot start one. site_id is OPTIONAL when OAuth-authenticated. This is the external competitor lens (third-party SERP data); for YOUR OWN search performance use get_keyword_performance, and for your content playbook use get_content_actions.

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• fleet_gsc_query

  Heista

  LIVE Google Search Analytics query — group by any dimensions (date, page, query, country, device, searchAppearance; up to 3) with page/query filters over up to 16 months of history. Richer than the snapshot tools: use this for ad-hoc analysis. NOTE: including the "query" dimension omits anonymized rare queries — use ["date"] or ["page"] for complete totals on low-traffic sites. Hard cap 100 rows. Read-only.

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• search_google_xray

  LinkedIn MCP Server (Salesbot)

  Google X-Ray search for public LinkedIn profiles via Google operators (site:linkedin.com/in). Useful when you don't want to consume LinkedIn search limits, and it CAN target a specific person (put the name/company in `keywords`). Found profiles are saved into your contacts (in a 'Google X-Ray' list, deduplicated by profile URL). Returns JSON `{ found, saved, rejected_low_quality, contacts, … }` where each item in `contacts` has `contact_id`, `full_name`, `profile_url` (note: this tool returns `contacts`/`profile_url`, unlike search_linkedin_people which returns `results`/`linkedin_url`). Saved leads are UNVERIFIED cached snippets — run enrich_contacts before trusting the current company. To move them into the CRM, add them to a campaign with add_contacts_to_campaign (auto-creates CRM leads) or use a CRM tool like set_deal_stage.

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• list_integrations

  leadmarina

  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.

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• trending_stories_tool

  Santiment

  Fetch current trending crypto stories with sentiment analysis ## When to use vs `combined_trends_tool` Prefer this tool when only stories are needed: it is the cheap, fast path and has no per-tool rate-limit sub-cap. `combined_trends_tool` is a superset — same stories plus trending words, their context and AI-generated bull/bear summaries — but it calls an LLM, so it is slower and capped much lower per plan. Use it only when trending *words* or those summaries are actually needed, and never call both for the same question. ## Parameters - `time_period` - Time period for trending stories (e.g., '1h', '6h', '1d', '7d'). Defaults to '1h' (last hour). - `size` - Number of trending stories to return (max 10). Defaults to 10. ## Response - `trending_stories` - List of trending stories. - `time_period` - Time period for trending stories. - `size` - Number of trending stories to return. - `period_start` - Start time of the time period. - `period_end` - End time of the time period. - `total_time_periods` - Total number of time periods. ## Trending stories - `title` - Title of the story. - `summary` - Summary of the story. - `bearish_sentiment_ratio` - Bearish sentiment ratio. - `bullish_sentiment_ratio` - Bullish sentiment ratio. - `score` - Score of the story. - `query` - Query used to find the story. - `related_tokens` - List of related tokens. They have the format `BTC_bitcoin` - first part is the ticker, second part is the slug in Sanbase.

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• search

  Dados Abertos Senado BR MCP

  Searches the Brazilian Federal Senate open data (senators in office and active committees of the Senate and the National Congress) catalog and returns up to 10 matching documents as { id, title, url }, ordered by relevance (an empty list means nothing matched). This tool exists for the OpenAI Deep Research contract: ChatGPT deep research, company knowledge and research workflows over the Responses API require exactly the tools `search` and `fetch`. Pass one of the returned ids to `fetch` to read the document. For direct questions and for data (values, series, rankings) prefer the `senado_*` tools, which return the actual data with provenance — this is a catalog index, not a data query. Query: natural language or keywords, Portuguese or English; accents and case are ignored. Behavior: read-only and idempotent — the catalog comes from the public source and is cached in memory.

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• decode_ad

  Heista

  Decode a specific video ad URL into its full structural formula — beat-by-beat breakdown, hook classification, behavioral psychology stack, creative format, runtime performance signals (active days on Meta Ad Library when available), and per-cut visual data. Takes one video URL plus an optional idempotency_key. Returns a job_id immediately; poll with get_decode every 15s until status is "completed" (typically 45-60s end-to-end). Use this when the user pastes an ad URL, names a specific competitor ad, asks "decode this" or "break down this ad" or "what makes this ad work", or wants sentence-level fidelity to one specific winner before writing a script with generate_adscript. Supports Facebook Ad Library, TikTok, Instagram Reels, YouTube Shorts, and direct .mp4 URLs. Costs 15 credits for videos ≤60s, 20 credits for 61-120s. Do NOT use to browse the corpus or find ads by category — use decoder_intelligence or adformula_intelligence (both free) for discovery. Do NOT use for image ads or static creative.

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• combined_trends_tool

  Santiment

  Combined trends tool that fetches trending words, stories, and documents in parallel. This tool provides a unified view of all trending data - words with their documents and stories - in a single response across all crypto projects. ## When to use vs `trending_stories_tool` This is a superset of `trending_stories_tool`: same stories, plus trending words, their context and AI-generated bull/bear summaries. It calls an LLM, so it is slower and has a tighter per-tool rate-limit sub-cap than every other tool. If only trending stories are needed, call `trending_stories_tool` instead; set `include_words: false` / `include_stories: false` to drop a half that is not needed. Do not call both tools for the same question. ## Parameters - `time_period` - Time period for trending data (e.g., '1h', '6h', '1d', '7d'). Defaults to '1h' (last hour). - `size` - Number of items per category to return (max 30). Defaults to 10. - `include_stories` - Include trending stories in response. Defaults to true. - `include_words` - Include trending words in response. Defaults to true. ## Response - `trends` - Combined trending data containing stories and words. - `metadata` - Request metadata including time period, size, and included data types. - `errors` - Any non-fatal errors encountered during data fetching. ## Trending Data Structure ### Stories - `title` - Title of the trending story. - `summary` - Summary of the story. - `score` - Trending score. - `query` - Search query used to find the story. - `related_tokens` - List of related crypto tokens (format: "BTC_bitcoin"). - `bullish_sentiment_ratio` - Bullish sentiment ratio. - `bearish_sentiment_ratio` - Bearish sentiment ratio. ### Words - `word` - The trending word. - `score` - Trending score. - `slug` - Associated project slug (if word is project-related). - `summary` - AI-generated summary of discussions. - `bullish_summary` - Summary of bullish sentiment. - `bearish_summary` - Summary of bearish sentiment. - `positive_sentiment_ratio` - Positive sentiment ratio. - `negative_sentiment_ratio` - Negative sentiment ratio. - `neutral_sentiment_ratio` - Neutral sentiment ratio. - `positive_bb_sentiment_ratio` - Positive bull/bear sentiment ratio. - `negative_bb_sentiment_ratio` - Negative bull/bear sentiment ratio. - `neutral_bb_sentiment_ratio` - Neutral bull/bear sentiment ratio. - `context` - Related words that appear with this trending word. - `documents_summary` - AI-generated summary of related social media discussions.

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• generate_title_seo

  Misar.Blog MCP Server

  Generate 5 search-optimised article titles from a TOPIC OR KEYWORD, each with a keyword-strategy hint. Aims at high-volume, low-competition long-tail phrases and at AI answer engines (ChatGPT, Perplexity, Claude) as well as Google. Pick between the two title tools by what you have in hand: use this one when you have a topic or keywords and the article may not be written yet. Use suggest_titles when the draft already exists and you want titles drawn from its actual text. Passing `context` here does not make them equivalent — this one still optimises for the keywords you supply. Nothing is saved and no article is created or retitled; use update_article to apply a title. Requires an API key and consumes AI credits per call. Generative, so repeated calls return different titles.

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• list_ad_items

  mcp-server

  List the individual listing items of one ADS integration — the per-product rows for listing-based ad channels (e.g. Marktplaats and other classifieds, which create one ad per product). Some ad channels (e.g. Google Shopping) submit the whole product set in bulk rather than as individual listings and so have no per-item rows — they return an empty list; use ad_status / get_ad_report for those. Returns {integrationId, total, returned, items:[{itemId, koongoProductId, parentId, productType, status, channelStatus, listingId, listingUrl, hasErrors, errorCount}]}. Filter with koongo_status, channel_status, listing_id or product_id to find failures; page with limit / offset. Rows carry only identifiers + statuses (no gate); an item's actual attribute value + full error report come from get_ad_item_report. itemId is what you pass to get_ad_item_report / get_ad_item_history. ad_id is the integrationId from list_ads. project_id is OPTIONAL (inferred for a single-project customer; project_id_required otherwise — then call list_projects).

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• google-trends.categories

  Vee3

  List all Google Trends category and subcategory labels you can pass to other Google Trends tools in the category field. Returns cat (array of category names, including All categories) and msg. Use this before interest-over-time or interest-by-region calls when filtering by category. Cost = 5 tokens.

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• getMarketOverview

  qubitsok — Quantum Computing Jobs, Papers & Researchers

  Get a snapshot of the quantum computing landscape — no parameters needed. Use when the user asks broad questions like "how's the quantum job market?", "what are trending topics?", or wants an overview of the quantum computing industry. Returns: total active jobs, top hiring companies, jobs by role type, papers published this week, total researchers tracked, and trending technology tags. For specific job/paper/researcher searches, use the dedicated search tools instead.

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• generate_title_seo

  Misar.Blog MCP Server

  Generate 5 search-optimised article titles from a TOPIC OR KEYWORD, each with a keyword-strategy hint. Aims at high-volume, low-competition long-tail phrases and at AI answer engines (ChatGPT, Perplexity, Claude) as well as Google. Pick between the two title tools by what you have in hand: use this one when you have a topic or keywords and the article may not be written yet. Use suggest_titles when the draft already exists and you want titles drawn from its actual text. Passing `context` here does not make them equivalent — this one still optimises for the keywords you supply. Nothing is saved and no article is created or retitled; use update_article to apply a title. Requires an API key and consumes AI credits per call. Generative, so repeated calls return different titles.

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• gdelt_get_tv_trending

  gdelt-mcp-server

  Retrieve trending topics, keywords, and phrases currently dominating US television news across national networks. No query required — returns the top memes of the present news cycle. Updated every 15 minutes. Note: the GDELT TV archive feed stopped updating around October 2024; results from this endpoint reflect that most-recent archived data rather than a live feed.

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• seo_keyword_google_ads_volume

  Seo Keywords Ads

  Exact Google Ads search volume for `<keyword>` — Google's own monthly search-volume numbers (plus competition and CPC) from the Ads API, for up to 10 keywords. Use when you specifically need Google Ads figures; for general SEO volume + keyword difficulty, prefer seo_keyword_overview (cheaper). Example: seo_keyword_google_ads_volume({ keywords: ["running shoes"], location_code: 2840, _apiKey: "your-base64-key" })

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• sonar_app_rankings

  sonar

  Rank history for an app's tracked keywords — daily ranks over the requested window, one history array per keyword. Use this to check how rankings moved after a metadata change or to find keywords trending up or down. Cursor-paginated over keywords (default 50 per page). Requires an Indie plan (trial counts).

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• list_websites

  RedReplier

  List all monitored websites for this account, each with its keywords (value + status: PENDING, ACTIVE, DISABLED, SUSPENDED). Start here — you need website IDs and keyword IDs for most other tools.

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• waveguard_scan

  WaveGuard

  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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• facebook_ad_library_search_companies

  captapi

  Find Meta Ad Library pages by brand — name-matched, pageId for company-ads (not profileId). Costs 2 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

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