"Tools or methods to perform deep data analysis" matching MCP tools:

• patent_landscape_async

  mcp-knowledge

  Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.

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• semantic_search

  DC Hub — Data Center Intelligence MCP Server

  Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 16,900+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".

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• load_fundamental_workflow

  Shibui Finance

  Load fundamental workflow for valuation, cash flow, margins, balance sheet. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about company valuation, "is X a good buy", financial health, debt levels, profitability ratios, revenue trends, earnings quality, or any deep-dive company analysis. Can be combined with other workflow tools.

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• patent_landscape_async

  gapup-mcp

  Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.

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• search

  UseMyContext

  Search the user's files by filename and return matching documents in the deep-research result shape. ALIAS: this is the SAME search as search_files (same data, same permissions) - use it when your client requires the id/title/url search contract (ChatGPT deep research); otherwise prefer search_files for richer file metadata. Each result's id can be passed to fetch (or get_file) to read that document. Read-only; always allowed.

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• scaffold_service

  @imqueue

  READ-ONLY: returns generated source code as text and writes nothing to disk, creates no project and runs no command. Generates an idiomatic @imqueue/rpc service (an IMQService subclass with @expose()d, JSDoc-typed methods) plus a bootstrap that starts it. Provide the methods you want, or omit them for a starter template. Any non-primitive parameter or return type also gets a types.ts with the required @classType()/@property() declarations — without those the generated client types it `any`, which compiles. Use create_service (local install only) if you want files actually written.

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• patent_landscape_async

  gapup-mcp

  Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.

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• strale_execute

  Strale - 290+ API capabilities for AI agents

  Executes a Strale capability by slug and returns the result. Use this when you need to perform any verification, validation, lookup, or data extraction from the capability registry. Call strale_search first to find the right slug and required input fields. Returns a result object with the capability output, latency, price charged, and data provenance. Several capabilities are free without an API key (10/day limit) — strale_search reports which. Paid capabilities debit from the wallet — check strale_balance first for high-value calls.

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• deltasignal_readiness

  DeltaSignal ATLAS-7

  Use this read-only tool before analysis to verify that the DeltaSignal ATLAS-7 data plane is live, fresh, and safe to query. It returns service readiness, active source dates, issuer coverage, quality coverage, debt coverage, live-price status, market regime, and tower-coherence diagnostics. Parameters: none; call it exactly as-is when the user asks if DeltaSignal is ready or whether data freshness is acceptable. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, does not write external systems, and does not handle secrets or payments itself. Use it at the start of an agent workflow, after a deploy, or whenever results should be gated on freshness; use daily_changes for what changed and issuer tools for company-specific analysis.

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• deltasignal_readiness

  DeltaSignal ATLAS-7

  Use this read-only tool before analysis to verify that the DeltaSignal ATLAS-7 data plane is live, fresh, and safe to query. It returns service readiness, active source dates, issuer coverage, quality coverage, debt coverage, live-price status, market regime, and tower-coherence diagnostics. Parameters: none; call it exactly as-is when the user asks if DeltaSignal is ready or whether data freshness is acceptable. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, does not write external systems, and does not handle secrets or payments itself. Use it at the start of an agent workflow, after a deploy, or whenever results should be gated on freshness; use daily_changes for what changed and issuer tools for company-specific analysis.

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• list_vision_reports

  switch

  List your Video Analysis history, newest first: report_id, date, status, source kind, duration, engine, tokens charged, and each report's headline. Use it to find a past analysis, then pass its report_id to get_vision_report (full report) or video_to_prompt (just the recreation prompt).

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• verify_claim

  Ground Truth - Fresh Evidence for AI Agents

  Verify a factual claim against specific public evidence URLs before an agent repeats it or acts on it. The tool checks whether supplied keywords appear in each fetched source and reports per-source evidence. It does not perform open-ended search, semantic contradiction analysis, or prove a claim true when a page is silent; choose direct evidence URLs and interpret the result as a support signal. Fetched pages are cached for 5 minutes.

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• t54_list_operations

  Agentic Swarm Marketplace (T54 x402 MCP)

  Returns operationIds, HTTP methods, paths, and query parameter names from the bundled OpenAPI spec (no network). Use before t54_x402_request or per-SKU tools.

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• audit

  mcp

  Perform comprehensive audit of a website URL. Fetches the URL content ONCE and provides a combined report with: - Classification: category, subcategory, language, sentiment, demographics - SEO Analysis: score, grade, issues, recommendations - EEAT Analysis: experience, expertise, authoritativeness, trustworthiness scores - AEO Analysis: AI answer engine optimization score, metrics, issues, signals (includes full Citation Readiness analysis in the nested 'citation' key) - Advertiser Matching: best-fit advertising networks with scores - Similar Sites: competitor/related sites from the same category This is more efficient than calling classify_url, analyze_seo, analyze_eeat, analyze_aeo, select_advertiser, and find_similar_sites separately as it only fetches the page once. Args: url: The website URL to audit (e.g., "https://example.com"). Returns: Comprehensive audit report with: - url: The analyzed URL - classification: Category, subcategory, language, sentiment, demographics - seo: Score, grade, issues, recommendations - eeat: EEAT score, grade, category scores, issues, signals - aeo: AEO score, grade, metrics, issues, signals (includes citation results) - advertisers: Matched advertising networks with scores - similar_sites: Related sites from the same category (up to 10) - cached: Whether result was from cache

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• malware_get_template

  website-search

  Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

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• load_fundamental_workflow

  Shibui Finance

  Load fundamental workflow for valuation, cash flow, margins, balance sheet. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about company valuation, "is X a good buy", financial health, debt levels, profitability ratios, revenue trends, earnings quality, or any deep-dive company analysis. Can be combined with other workflow tools.

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• load_comparison_workflow

  Shibui Finance

  Load comparison workflow for X vs Y, peer analysis, relative valuation. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to compare companies, "X vs Y", "how does X compare to Y", peer benchmarking, sector peers, side-by-side metrics, or relative valuation. Can be combined with other workflow tools.

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• get_full_text

  Pubmed

  Fetch the FULL TEXT of a biomedical paper from PubMed Central (the open-access subset) by PubMed ID. PREFER OVER get_abstract when you need methods/results/discussion, not just the abstract — "read the full paper", "what methods did <PMID> use", "extract details from the paper". Resolves the PMID to its PMC id and returns the article body text (capped ~40k chars). Only open-access articles are in PMC — returns has_full_text:false (use get_abstract) otherwise.

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• free2aitools_rank

  Free2AITools

  Keyword-search AI entities using the task/query text as input and return FNI-ranked catalog entries. Mechanically this is the same keyword search as free2aitools_search with the task text folded into the query; it does NOT perform task-fit recommendation, compatibility analysis, model inference, or model execution, and it is NOT an inference router. USE WHEN you have task text and want catalog entries ordered by FNI. The caller makes the final selection; results are never paid placement and there is no billing. Read-only, no side effects. May return a retryable transient 503 under cold-path or fallback budget limits; retry according to Retry-After. Use free2aitools_search for plain keyword discovery, or free2aitools_select_model to apply hardware/license metadata filters.

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• arena_get_strategy_performance

  Backtesting Arena

  Aggregated backtest performance for ONE specific (strategy, asset, interval) combination. Returns run_count, avg_cagr, avg_win_rate, avg_drawdown, effective_years, vs_buy_hold comparison (beats_buy_hold, cagr_delta) and an `evidence` block declaring the gate machine-readably (gate_applies_to: stats.run_count, threshold 5 runs, benchmark value, aggregation data window). For multi-strategy overview use arena_get_strategy_insights. Use this to answer 'How does strategy X perform on asset Y?'. [Free tier]

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