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213,552 tools. Last updated 2026-06-19 19:10

"Using Google Scholar for Conducting Deep and Critical Literature Reviews" matching MCP tools:

  • Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).
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  • List countries and region codes you can pass as location on google-search.keyword_traffic_insights and google-search.url_traffic_insights. Returns an array of entries with country_name and country_code (for example US, GB). No request parameters. Successful calls use 5 API tokens.
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  • 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. Found profiles are saved into your contacts (in a 'Google X-Ray' list, deduplicated by profile URL) and the tool returns their contact_id values. 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. Paginates Google results and auto-filters duplicates.
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  • Lists directly accessible Google Ads customers for the configured Google Ads credentials, including descriptive names when Google returns them. Use this to discover customer IDs before running Google Ads hierarchy or reporting tools.
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  • Pro-tier. Fetch and extract a web page, then audit it against the Proximens Oracle GEO principles using pgvector semantic matching plus category-specific heuristic checks (structured data, robots/crawler access, content depth, freshness, E-E-A-T, multimodal). INPUT: url (required, http/https); optional mode ("fast" = heuristic signal checks, returns in seconds — the default; "deep" = full Gemini-synthesized consultancy report in Dutch with 7-dimension scorecard and sector benchmark, takes ~30-50s), client_name (report header), branche_hint ("main:sub", e.g. "health_wellness:yoga_studio"), max_issues (1-25, default 10). RETURNS: JSON with a 0-100 score, severity-ranked issues (critical/major/minor) each with a finding and an actionable suggestion, top recommendations, and a markdown report; deep mode additionally returns score_set (7 GEO dimensions), sector (benchmark cohort), and a full consultancy-grade report_markdown (deep_mode="timeout_fallback" means the synthesis exceeded its budget and the fast result was returned instead). USE fast mode for quick checks and bulk triage; USE deep mode when you need a client-ready audit report. Free tier is blocked.
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  • Logic-trace driver-chain explorer — answers "WHY is this activity critical?" and "WHAT does it drive?". Traces driving predecessors backward from a target activity to project start (the "why critical" chain) and/or driving successors forward to project finish (the "what it drives" chain). Detects constraint-driven artificial criticality and cites AACE RP 24R-03 §4 when found. Supports multiple parallel critical paths (MCPM) and near-critical paths. Use this tool when investigating a single activity's logic chain. For a project-wide CP / logic health audit, use ``critical_path_validator``. Args: xer_path: server-side path to the schedule XER. xer_content: full text of the schedule XER (alternative for hosted/remote use). Supply EXACTLY ONE of path/content. target_activity_codes: list of task_codes to trace; if empty, all CP / near-critical endpoints are traced. direction: 'backward' (predecessors), 'forward' (successors), or 'both' (default). include_near_critical: also trace near-critical endpoints (within float band). output_dir: optional dir for HTML / CSV / JSON outputs. Returns: { "paths": [{chain dicts ...}], "output_files": {dashboard, csv, json}, "project_finish": "YYYY-MM-DD", "project_name": ..., "data_date": ... }
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Matching MCP Servers

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    An MCP server for searching Google Scholar, enabling paper search, author lookup, citation tracking, and BibTeX export for AI assistants and automation workflows.
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    Enables academic research through Google Scholar by searching for papers, finding author publications, discovering recent research, and identifying highly cited works through web scraping with natural language queries.
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    MIT

Matching MCP Connectors

  • Search Google Scholar for academic papers, citations, and author profiles.

  • Resolve scholarly identifiers (DOI, PMID, ISBN, arXiv, ISSN, ADS, WHO IRIS) into citations (10,000+ CSL styles) and exports (BibTeX, RIS, EndNote...), plus retraction, open-access, and citation-fabrication checks. Six tools, anonymous-friendly Streamable HTTP.

  • Search Google Scholar for academic papers, citations, and scholarly articles. Returns results with titles, authors, publication info, citation counts, and links to PDFs. Use cites parameter to find papers citing a specific work, or cluster to find all versions of a paper. For US court opinions and case law, use google_scholar_cases instead.
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  • Query Google Scholar for academic papers, citations, and research articles across all disciplines. Returns paper title, authors, publication venue, citation count, abstract preview, and full-text link if available. Use for comprehensive literature searches, citation tracking, or finding highly-cited works.
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  • Get details for one Google Maps review. Provide review_id from a place reviews response. Returns one review object at the top level with fields such as review_id, review_text, rating, and user_name when available. Additional upstream fields may appear. Successful calls use 2 API tokens.
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  • "Hours / phone / reviews of [business]" / "Google business info for [place]" / "is [restaurant] open" — full details for a Google Place: address, phone, hours, website, ratings, user reviews. Requires a place ID from `maps_place_search`. Use after search to drill into one specific business.
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  • Resolves a list of Google Maps URLs into canonical Google Maps Place IDs. **When to call this tool (CRITICAL):** * Use this tool when the user provides one or more Google Maps sharing links or URLs (e.g. 'https://maps.app.goo.gl/...', 'https://www.google.com/maps/place/...', or 'https://maps.google.com/...') and you need to extract the underlying canonical Place IDs. * You can specify up to 20 URLs to resolve in a single batch request. **Input Requirements (CRITICAL):** * **`urls` (array of strings - MANDATORY):** The list of Google Maps URLs to resolve. Each URL must be a valid, single-place Google Maps URL. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some URLs resolve successfully while others fail). * The output list of `entities` is guaranteed to map 1:1 with the input `urls` indices. A failed URL resolution will result in an empty `Entity` message (no fields are set) at its corresponding index in the `entities` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific URL index failed. The key of `failed_requests` represents the 0-based index of the failed URL in the request. Do not assume the entire batch call failed because of a partial failure.
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  • Find papers SIMILAR to a given article — NIH PubMed's own computed 'related articles' (pubmed_pubmed neighbors), ranked by relevance using shared terms/MeSH/citations. Pass one PMID; returns the top related papers with full citation metadata (title, authors, journal, date, DOI). Use for "more papers like this", building a reading list from a seed paper, or broadening a literature search beyond keyword matches. Distinct from get_citations (which finds papers that cite this one).
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  • Map the full dependency tree of an npm package and identify CRITICAL supply chain risks at every level. Unlike auditing a flat list of packages, this tool traverses the dependency graph — showing not just your direct dependencies but also what your dependencies depend on. Hidden CRITICAL packages (sole publisher + >10M weekly downloads) often lurk 1-2 levels deep. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads — sole point of failure for a massive attack surface - HIGH: sole publisher + >1M/wk, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) depth=1 (default): root package + all direct dependencies depth=2: also traverses one more level for any CRITICAL/HIGH direct deps (reveals hidden exposure) Examples: - audit_dependency_tree("express") — see all of Express's deps and their risk scores - audit_dependency_tree("langchain", 2) — reveal transitive CRITICAL deps 2 levels deep - audit_dependency_tree("@anthropic-ai/sdk") — audit Anthropic SDK full tree Use this when someone asks: - "What am I really depending on?" - "Are my dependencies' dependencies safe?" - "Show me the full supply chain risk for package X"
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  • Look up an IPv4 against the GreyNoise Community dataset. Returns noise (is the IP scanning the internet?), riot (is it a known good service like Google/Microsoft?), classification (malicious | benign | unknown), name, last-seen date, and a deep link. Useful for noise-suppression in SOC alerts.
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  • Resolves a list of Google Maps URLs into canonical Google Maps Place IDs. **When to call this tool (CRITICAL):** * Use this tool when the user provides one or more Google Maps sharing links or URLs (e.g. 'https://maps.app.goo.gl/...', 'https://www.google.com/maps/place/...', or 'https://maps.google.com/...') and you need to extract the underlying canonical Place IDs. * You can specify up to 20 URLs to resolve in a single batch request. **Input Requirements (CRITICAL):** * **`urls` (array of strings - MANDATORY):** The list of Google Maps URLs to resolve. Each URL must be a valid, single-place Google Maps URL. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some URLs resolve successfully while others fail). * The output list of `entities` is guaranteed to map 1:1 with the input `urls` indices. A failed URL resolution will result in an empty `Entity` message (no fields are set) at its corresponding index in the `entities` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific URL index failed. The key of `failed_requests` represents the 0-based index of the failed URL in the request. Do not assume the entire batch call failed because of a partial failure.
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  • Use when assessing consumer finance risk, benchmarking complaint volume against peers, or conducting pre-acquisition due diligence on a financial institution. Returns CFPB complaint rollups by company and product — volume, issue themes, and response rate trends. Example: Regional Bank X — 847 CFPB complaints in 2023, 34% on mortgage servicing, complaint volume 2.3x peer median — elevated consumer protection risk signal. Source: CFPB Consumer Complaint Database synced data.
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  • Get guest reviews for a specific hotel. Use this to help users understand what other guests thought about a hotel. Returns up to 10 recent reviews with ratings and comments. Args: hotel_id: The hotel's Vervotech property ID (from search results). Returns: Formatted list of guest reviews with author names, ratings, and review text.
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  • Research any topic — search Google, Bing, YouTube, X/Twitter, Amazon, Yelp, Google Trends, news, and 100+ more engines. Read webpages, extract video transcripts, find reviews, track competitors. Works without a domain.
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  • Evidence-graded MEDICAL literature search (PubMed + Europe PMC). Unlike search_all (generic, ranks high-cited reviews/guidelines above trials), this filters by research type via PubMed Publication-Type tags and re-ranks by the evidence pyramid (meta-analysis / systematic review > RCT > cohort > ...), so the actual clinical trials surface first. Open-access full text is pulled from Europe PMC by PMID. `query` should be English keyword/boolean text (PubMed maps it); do natural-language/multilingual understanding upstream. Returns hits with pmid/doi/study_type/evidence_level/citations/abstract and, when open-access, fulltext.
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  • Generate a deep link to a curated Event Escapes PACKAGE detail page (/packages/{slug}). Packages are hand-curated bundles of event tickets + hotel + experiences with savings vs DIY booking. Use this AFTER calling search_packages to surface a specific package to the user. This does NOT make a reservation - the user reviews tier/duration/guest selectors and books on the package page.
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