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"Enterprise-level Confluence search page supporting version 9.4.11" matching MCP tools:

  • Returns a paginated list of domains from the tracker database. Results are ordered alphabetically by domain name and support cursor-based pagination for full traversal. Filtering by category and minimum score allows targeted data extraction. Use this tool when: - You want to enumerate all known ad-tech or analytics domains above a risk threshold. - You need a dataset of tracker domains for offline analysis. - You are paginating through a category to build a block list. Do NOT use this tool when: - You need data for a specific domain — use `get_domain` instead. - You are searching by keyword — use `search` instead. - You want domains belonging to a specific company — use `get_entity` instead. Inputs: - `category` (query, optional): Filter by surveillance category. One of: `ad_tech`, `analytics`, `social`, `fingerprinting`, `content`, `cdn`, `other`. - `min_score` (query, optional): Integer 0-100. Exclude domains scoring below this value. - `limit` (query, optional): Number of results per page. Max 100 (paid), 20 (free). Default 50. - `cursor` (query, optional): Pagination cursor from the previous response's `next_cursor` field. Returns: - Array of domain list items (domain, category, score, prevalence, entity summary). - `meta.has_more`: true if more pages exist. - `meta.next_cursor`: pass as `cursor` to get the next page. - `meta.count`: number of results in this page. Cost: - Free tier: up to 20 results/page, 50 req/day. Pro/enterprise: up to 100 results/page. Latency: - Typical: <200ms, p99: <500ms.
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  • Returns a paginated list of corporate entities in the TunnelMind surveillance database. Includes data categories, estimated data value, and industry classification. Useful for enumerating the surveillance ecosystem by sector. Use this tool when: - You want to enumerate all entities in a specific industry (e.g., all ad-tech companies). - You need a dataset of surveillance entities for analysis or reporting. - You are building a comprehensive surveillance landscape map. Do NOT use this tool when: - You need the full profile of a specific entity — use `get_entity` instead. - You are searching by entity name — use `search` instead. - You need domain-level data — use `list_domains` instead. Inputs: - `industry` (query, optional): Filter by industry classification. Examples: `ad_tech`, `analytics`, `data_broker`, `social`, `crm`. - `limit` (query, optional): Results per page. Max 100 (paid), 20 (free). Default 50. - `cursor` (query, optional): Pagination cursor from previous response's `next_cursor`. Returns: - Array of entity list items (slug, name, parent_company, industry, data_categories, data_cost_usd). - `meta.has_more` and `meta.next_cursor` for pagination. Cost: - Free tier: up to 20 results/page, 50 req/day. Pro/enterprise: up to 100 results/page. Latency: - Typical: <150ms, p99: <400ms.
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  • Retrieves direct links to STRING evidence pages for protein–protein interaction pairs. Use this tool only when a STRING evidence page/link is needed. To determine whether an interaction is supported, use `string_interactions_query_set`. It returns URLs linking to STRING’s evidence pages, which display the underlying data sources (experimental results, publications, and curated databases) supporting each predicted interaction. A URL can be generated even for unsupported pairs; the URL is not itself an interaction verdict. Parameters: - **identifier_a**: Query protein identifier (Protein A) - **identifiers_b**: One or more target protein identifiers (Protein B), separated by `%0d` - **species**: NCBI taxonomy ID (e.g. `9606` for human or `10090` for mouse) Typical user questions that should trigger this tool: - "Can you show me the STRING evidence for this interaction?" - "Show me the details supporting this interaction." - "What supports the interaction between TP53 and MDM2?" - "Where can I find the STRING evidence for this pair?"
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  • Check whether a factual claim is supported by a specific set of public evidence URLs that you already have. For each source, the tool performs a case-insensitive keyword match over the fetched page body, then marks that source as supporting the claim when at least half of the supplied keywords appear. Use this for evidence-backed claim checks on known pages, not for open-ended search, semantic reasoning, or contradiction extraction. The aggregate verdict is driven only by the per-page keyword support ratio. Fetched pages are cached for 5 minutes.
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  • Fetch a historical time series of daily market-level snapshots (overall market sentiment, not a single ticker). Call this when the user asks how the overall market mood/regime has trended over time, wants to chart market α-sentiment / z-score over a window, or needs a range of daily market snapshots to compute averages or momentum. Optional: `days` (1-1000, default 30; tier may cap lower). For a single ticker's history use get_ticker_history instead. Tier caps on `days`: free=7, alpha=365, pro=730, enterprise=1000. The `date` parameter (end-date anchor) is only honored for enterprise tier — for all other tiers it is silently ignored and the window always ends at the most recent available snapshot. Returns: array of daily market snapshots (oldest first), each with snapshot_date plus all standard MarketSnapshot fields. Response also reports tier_cap, effective_days, start_date, end_date and date_param_honored.
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  • Search for known disciplinary actions against a physician (suspension, revocation, surrender, probation). Sourced from state medical board status text. Use this when: - Pre-employment screening - Recredentialing — required by most insurance contracts - Investigating a referral source Input: NPI (preferred) OR full name. Optional state filter. Output: array of {state, action_type, date, source_url}. Action types: suspension | revocation | surrender | probation | reprimand | other. Coverage note: this surfaces board-status-level signal. Underlying PDF documents are on the roadmap. Paid tier only (Pro or Enterprise).
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  • Confluence MCP — wraps the Confluence Cloud REST API v2 (OAuth)

  • Create, edit, preview, publish, and manage web pages from MCP-capable AI clients.

  • Return how ONE page's Google Search performance changed over time (FD-040) — the time-axis drill-down for a page surfaced by get_breakdown(dimension='page'). Given a `page` (a normalized path like '/news/rps-revenue-per-session-guide' or a full URL — both resolve), returns a `series` of day or week buckets, each with clicks, impressions, and impression-weighted avg_position, plus a `summary` (first/last/best/worst position, position_delta, click & impression totals). avg_position is a RANK: smaller is better, so a NEGATIVE position_delta means the page's ranking IMPROVED over the window (e.g. 12.0 → 9.0 = delta −3.0). Use this to verify whether SEO work on a page paid off (rank rose / clicks grew) or slipped. Buckets where the page never appeared in search are omitted (gaps), so the series can be shorter than the period. `granularity` defaults to 'day' for windows up to ~35 days and 'week' for longer (weekly smooths daily noise); pass it to override. site_id is OPTIONAL when OAuth-authenticated. Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). Google-search only; data lags 1-2 days. This is per-page; for the cross-page snapshot use get_breakdown(dimension='page'), and for per-query (keyword) trends use get_keyword_performance.
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  • Full-text search across Maven Central packages by groupId, artifactId, version, or tags. Returns artifact coordinates, latest version, and download timestamps for up to 200 matches.
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  • Return the ENTIRE corpus including premium resource bodies in one document — the keyed deliverable of the Corpus/Enterprise license. Requires a Corpus- or Enterprise-tier api_key (a Starter key unlocks premium resources but NOT the corpus file); without an entitled key a payment-required/upgrade object is returned. The free, premium-stubbed version is get_corpus.
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  • Full-text book search across Open Library works. Supports field filters (title, author, subject, publisher, ISBN, language) and returns work-level records with edition counts, cover IDs, and reading availability. Use query for general search or combine specific field filters. Results are work-level — drill into editions via openlibrary_get_editions.
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  • Initiate an OAuth handoff to a vendor integration (Google Ads, GA4, Search Console, Sheets, Drive, BigQuery, Meta Ads, Jira, Confluence). Returns an authorization URL the user opens in a browser. After the user clicks Allow, the connection is created and you can poll check_integration_status(handoff_id) to find out when the data is ready.
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  • Return the ENTIRE corpus including premium resource bodies in one document — the keyed deliverable of the Corpus/Enterprise license. Requires a Corpus- or Enterprise-tier api_key (a Starter key unlocks premium resources but NOT the corpus file); without an entitled key a payment-required/upgrade object is returned. The free, premium-stubbed version is get_corpus.
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  • Near-duplicate page PAIRS that share a near-identical passage (real merge/redirect candidates) for wiki hygiene. Optional space_id restricts to one space; threshold (0..1, default 0.92) is the minimum chunk-level similarity to count as a duplicate.
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  • Replace an existing page with full new content. Requires base_version_hash (from get_page) to prevent accidental overwrites — send force: true to skip this check. For small changes, use patch_page instead — it saves tokens and preserves version history.
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  • [Read] Aggregate per-coin social sentiment for a time range: overall sentiment, positive/negative split, mention count, and sample tweets. X/Twitter post search or tweet-level evidence -> search_x. Multi-platform social thread search -> search_ugc.
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  • Given a product ID, find similar products across the entire catalog. Useful for "more like this" recommendations or finding alternatives. Returns compact product cards, not full variant detail; call get_product for SKU-level variants, exact variant prices, merchant description, store info, and all images. Returns page and hasNextPage. Returns up to 20 results per page, paginated (max 3 pages).
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  • Structured diff showing what would be deployed if the user ran tfdeploy now. Returns component-level changes (added/removed/modified), field-level details, and pricing deltas. Defaults (#1392): with no version arguments, compares the LAST SUCCESSFULLY DEPLOYED version against the user's CURRENT LIVE DESIGN (the same data the UI shows). Empty baseline if nothing has been deployed or after a destroy. Pending drafts are NOT used as the target — they go stale once the user edits past them; live IR via chat history is always current. Pass explicit `from_version` and/or `to_version` integers to compare any two saved versions (e.g. v3 → v5). REQUIRES: session_id from convoopen response (format: sess_v2_...).
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  • Top Gainers (Alpha-Ranked): Today's biggest 24h gainers across the CoinGecko top-1000 universe (stablecoins and wrapped BTC/ETH derivatives filtered out) plus per-chain ecosystem gainers for Ethereum, Base, Arbitrum, BNB Chain, Polygon, and Optimism — RANKED BY CROSS-SIGNAL ALPHA CONFLUENCE, not raw % move. Each gainer is scored by how many independent signals corroborate it (whale accumulation, cross-chain DEX trending, social/CT hype, sector rotation, multi-timeframe chart trend, AI forecast); tokens with real confluence lead and pure price-pumps are demoted. Returns: alphaRanked[] (symbol, verdict, signalCount, per-signal badges + evidence), rawMovers[] (no-confluence pumps), losers, and per-chain breakdown. Optional { params: { chain } } drills into one chain. Reads cached signals (zero extra API cost) with graceful degradation. Use to find what's actually worth attention, not just what's pumping.
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  • Browse the Czech Statistical Office (ČSÚ) open-data catalog of datasets ('datové sady'). Returns id (kod), version (verze), Czech title (nazev), status, and available time/territory levels. The full catalog is ~781 datasets; filter by a case-insensitive substring of the Czech title (the API has no server-side search) and page with limit/offset.
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  • Get detail for a CoreClaw worker. WHEN TO USE: Use before running a worker to inspect version, README, and parameters. 中文触发: 当用户要在 CoreClaw 中查询、运行、重跑、停止、导出或查看对应 worker/run/task 数据时使用。 WHEN NOT TO USE: Do not use public web search or code search for private CoreClaw platform data. Do not call excluded internal worker-version or internal-detail APIs. RETURNS: JSON with worker name, username, version, readme, and parameters. WORKFLOW: Follow with get_worker_input_schema and then run_worker.
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