"Tools for Data Analysis" matching MCP tools:

• deltasignal_readinessA

  DeltaSignal ATLAS-7B

  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.

  ConnectorNo auth

• fleet_gsc_queryA

  HeistaA

  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.

  ConnectorNo auth

• discover_toolsA

  Data NantesA

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

  ConnectorNo auth

• lookup_restaurantA

  Seemor Restaurant IntelligenceA

  Look up a specific restaurant by its Seemor ID. Returns grade, summary, cuisine, neighborhood, and other details. Use the fields parameter to request richer data (standard or premium; fully analyzed restaurants only). coverage_level 'full' rows carry a letter grade; 'basic' rows are Seemor quick reads: review-analysis bands (grade null, preliminary_band such as 'B-range') with a one-line tldr, graded from review analysis rather than star ratings; 'none' rows have no analysis yet. Use search_restaurants or find_restaurant first to get restaurant IDs. Use this for a single place the user asks about, not for every result of recommend.

  ConnectorNo auth

• deltasignal_readinessA

  DeltaSignal ATLAS-7C

  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.

  ConnectorNo auth

• get_statusA

  mcp-serverA

  Poll the status of either a data spec's own process (schema inference + code generation, run by start-analysis — pass specId, reaches "ready" or "failed") or a data-load job (pass jobId, reaches "complete" or "failed"). Pass exactly one of specId or jobId. Right after create-spec/update-spec + start-analysis, poll by specId; once that reaches "ready", its response's lastJobId (if present) points at the data-load job — poll that separately by jobId for load progress.

  ConnectorOAuth

• semantic_searchA

  DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, FiberA

  Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 20,500+ 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)".

  ConnectorNo auth

• tech_fingerprintA

  ContrastAPIA

  Detect website technology stack: CMS, frameworks, CDN, analytics tools, web servers, languages (via HTTP headers + HTML analysis). Use for passive reconnaissance; for full audit use audit_domain. Free: 30/hr, Pro: 500/hr. Returns {technologies: [{name, category, confidence%, version}]}.

  ConnectorNo auth

• malware_get_templateA

  website-searchA

  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.

  ConnectorNo auth

• __unlock_blockchain_analysis__A

  mcp-serverA

  Initializes a Blockscout MCP session: returns server reference data, the `blockscout-analysis` skill pointer, and the URI resolution rule. Call this tool exactly once per session, before any other tool, and reuse its payload for the rest of the session; do not call it again.

  ConnectorNo auth

• deep_auditA

  x402-data-gatewayA

  Run one read-only AI-search-readiness audit for a public business domain: company, technology, contact, and DNS/email evidence from `enrich`, plus the live structured-data gap analysis and paste-ready JSON-LD template from `schemaforge`. Use `enrich` for company facts only or `schemaforge` for structured-data remediation only. The template contains placeholders for real data; the score is diagnostic, no site changes are made, and it does not guarantee AI citations.

  ConnectorNo auth

• search_statisticsA

  Fodda Topic & Trend ResearchA

  HARD NUMBERS only: specific figures, market sizes, growth rates, and quantitative data points across Fodda's knowledge graphs. Each result links back to the expert trend it supports. Use when a question asks for a number or statistic — try this BEFORE supplemental data tools, as Fodda's experts may have already curated the answer. For expert quotes, editorial analysis, and narrative interpretation, use search_insights instead. Works on ALL graphs — domain, expert, and report. Search multiple graphs for best coverage.

  ConnectorOAuth

• preview_synthetic_breach_reportA

  Breach402 Owner ProtectionA

  Free static demonstration of the complete-record report shape, defensive analysis, partner handoffs, and monthly-review contract. Contains no real owner or breach data and performs no lookup.

  ConnectorNo auth

• initiate_analysisA

  StockLensA

  Initiate a full StockLens AI analysis for a specific stock. Starting a new run may consume one Analysis credit (LENS_AI) or one Plus Analysis credit (LENS_AI_PLUS, which may add AI narratives). Returns an analysis_id immediately — completion is asynchronous. Retrieve status or results with a separate fetch_analysis_result call when the user asks for them. A recent matching analysis may be reused; the receipt explicitly reports new_run_started and reused_existing without claiming an asynchronous credit charge has completed. Concurrent identical initiations receive retry guidance. Free supports the standard Analysis only; Pro and Max unlock Plus Analysis. Does NOT screen, rank, or compare across multiple stocks — call discover_stocks for any multi-stock or "top N" request. Does NOT execute trades, place orders, or move funds. Does NOT accept more than one ticker per call.

  Connector

  Destructive

  No auth

• semantic_searchA

  DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, FiberA

  Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 20,500+ 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)".

  ConnectorNo auth

• discover_toolsA

  Data Economie FrA

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

  ConnectorNo auth

• discover_toolsA

  Bright DataA

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

  ConnectorNo auth

• analyze_stockA

  HPSILab Quant FinanceA

  Aggregate all quant tools into one JSON stock analysis. The tool reuses the existing MCP tools as its data sources, then derives a direction signal, direction score, bullish factors, bearish factors and plain-English summary. If one underlying tool is gated, unavailable or raises an error, the remaining tools still contribute to the final result (status "partial"); if every underlying tool fails, the whole call fails (status "error", isError=True) instead of a misleadingly "successful" empty analysis. Args: symbol: Stock symbol, e.g. "NVDA". refresh: Request fresh IV Radar data instead of using the backend's fresh IV cache. Defaults to False.

  ConnectorNo auth

• mlp_infoA

  MLP Tax Computation EngineA

  Returns reference data for a supported MLP ticker — current cash distribution per unit, distribution growth CAGR, default return-of-capital percentage, distribution coverage ratio, K-1 entity count, operating-state count, and last-verified date. Use when: User wants to look up baseline characteristics of an MLP before modeling — e.g., comparing distribution coverage across partnerships, checking how many K-1 entities a holding generates for tax-prep complexity, or seeing the operating-state count for state-tax filing-burden estimation. Don't use for: Tax computation. Use mlp_projection (long-horizon modeling), mlp_estate_planning (estate analysis), mlp_sell_vs_hold (break-even sell price), or k1_basis_compute / k1_basis_multi_year (computing basis from actual K-1 data). Note: This tool returns reference data only — no IRC citations apply, no methodology disclosure attached. For computation, use the modeling tools above. Maintained by Lucas Andersen, MS Finance.

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• mlp_infoA

  mlp-taxA

  Returns reference data for a supported MLP ticker — current cash distribution per unit, distribution growth CAGR, default return-of-capital percentage, distribution coverage ratio, K-1 entity count, operating-state count, and last-verified date. Use when: User wants to look up baseline characteristics of an MLP before modeling — e.g., comparing distribution coverage across partnerships, checking how many K-1 entities a holding generates for tax-prep complexity, or seeing the operating-state count for state-tax filing-burden estimation. Don't use for: Tax computation. Use mlp_projection (long-horizon modeling), mlp_estate_planning (estate analysis), mlp_sell_vs_hold (break-even sell price), or k1_basis_compute / k1_basis_multi_year (computing basis from actual K-1 data). Note: This tool returns reference data only — no IRC citations apply, no methodology disclosure attached. For computation, use the modeling tools above. Maintained by Lucas Andersen, MS Finance.

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• geometric_confidenceA

  governance-platformA

  Summarize an already-computed state_vector into a confidence level (high/medium/low) with a recommendation. Post-hoc digest - use analyze_anomaly or check_drift for fresh analysis of raw data.

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