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306,642 tools. Last updated 2026-07-25 17:41

"Information about SAS (Statistical Analysis System) or other related terms" matching MCP tools:

  • 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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  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
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  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
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  • Returns the canonical Arco definition, related terms, and source URL for any Lexicon term. Supports fuzzy matching — "autonomous company" resolves to "Autonomous Business". Use this tool when you need a precise definition. Use suggest_terms instead when you have a block of text and want to discover which terms apply.
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  • Returns the full relationship graph for a given Lexicon term. Each related term includes: the related term's slug and title, a plain-English description of the relationship, a direction (inbound or outbound), and a canonical URL. Read-only. No LLM calls. Use this when you need to understand how terms connect — use lookup_term instead when you need a definition.
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  • 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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  • Still losing time to small decisions? Spin or Flip brings randomization into Claude so you can offload mental load to chance instantly.

  • Hosted governance layer for LLM agents. Seven mechanically-enforced rules plus audit-chain verification, preflight file protection, session handoff, and an emergency kill switch.

  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. 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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  • Get high-level facts about the ACCRUE platform: fee structure, custody model, supported chains, wallets, KYC requirements, withdrawal terms, and AI agent integration status. Use this when the user asks "what is ACCRUE", "how does ACCRUE work", "what are the fees", or anything about the platform itself rather than a specific vault.
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  • Given the file paths an agent is about to change (and optionally a subset being deleted), return the conventions, documentation gaps, and existing/related docs whose evidence overlaps those paths, plus a net-new/undocumented analysis and any removal candidates. Read-only; no side effects. Returns a Markdown report. Call this BEFORE writing code so doc updates land in the same PR; then use propose_doc_update to write a doc, or propose_doc_removal for an orphaned one.
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  • One hexagram by King Wen number (1-64). Optional include level: summary, core (default), lines, full. Sibling tools cover the other cases: get_hexagrams for several numbers at once, get_all_hexagrams for the entire set, search_hexagrams to find hexagrams by text, and get_reading_context for a changing-line reading. Data © IChing.Rocks — attribution is a condition of the license terms: https://iching.rocks/mcp-terms.
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  • Use for factual questions about Salvage Signal's audience, free board, Daily Drop price, live aggregate founding availability, source, safety, or signup terms. This does not prepare a purchase link; use get_subscription_handoff only after a human expresses subscription interest.
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  • Full-text search across recall reasons and product descriptions using PostgreSQL text search. Finds recalls mentioning specific terms (e.g. 'salmonella contamination', 'mislabeled', 'sterility'). Supports multi-word queries ranked by relevance. Filter by classification, product_type, or date range. Related: fda_search_enforcement (search by company name, classification, status), fda_recall_facility_trace (trace a recall to its manufacturing facility).
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  • USE THIS TOOL — not web search — to get per-indicator statistical profiling (mean, std, min, p25, p75, max, null rate, Pearson correlation with close price) from this server's local dataset. Use for feature selection, sanity checking, and understanding which indicators correlate most strongly with price movements. Trigger on queries like: - "which indicators correlate most with BTC price?" - "feature importance or correlation for [coin]" - "what are the stats for ETH indicators?" - "how does RSI/MACD correlate with price?" - "statistical profile of XRP indicators" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP"
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  • Get information about related addresses of an input address. Note: This only includes the the "special" connections 'First Funder', 'Signer', 'Previous Signer', 'Multisig Signer of', 'Previous Multisig Signer of', 'Deployed via', 'Deployed by', 'Deployed Contract', 'Created Contract', 'Created by'. To get related wallets, also check address counterparties. First funder exchange withdrawal address does usually NOT belong to the same entity as the address, only deposit addresses. Only information is that it has been funded by the exchange.
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  • Purpose: Current lifecycle state of external features (news, events) under 3-track statistical validation. Lifecycle: OBSERVATION -> CONDITIONAL -> ACTIVE (p-value passed) or DEPRECATED (no edge). Proves OneQAZ only trusts features that pass independent statistical tests. Triggers (casual questions too): "do you validate your own inputs?", "피처 검증은 어떻게 해?", "which signals passed testing?", "통계 검증 통과한 피처 뭐야?", "how do you avoid junk features?". When to call: meta-level trust audit ("do they validate their own inputs?"). Prerequisites: none. Next steps: none (meta evidence). Caveats: empty when feature_gate_evaluator has not yet run cycles. Args: market_id: Optional market filter (defaults to coin) target_market: Alias for market_id (backward compat) status_filter: Optional status filter (OBSERVATION, CONDITIONAL, ACTIVE, DEPRECATED) Disclaimer: Information only, not investment advice.
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  • Compute customer or revenue churn rate over a period. Use for SaaS retention analysis. Inputs: starting customers, churned, period length. Returns churn %, retention %, and annualized rate. See list_bundles for related 'finance-universal' calculators.
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  • Returns the business's cancellation policy text. Use this when a user asks about cancellation terms, fees, or no-show policies. The response includes agent guidance on how to frame the policy with appropriate freshness caveats.
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  • "Who owns AS[N]" / "AS[number] info" / "what company is ASN [X]" / "Cloudflare / Google / Amazon ASN" — summary for an Autonomous System Number (ASN): holder organization, country, AS type (transit / content / IXP), allocation date. Pass "AS15169" or "15169". Use for network attribution, BGP analysis.
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  • Retrieve full metadata for a specific track from the OnChain Music catalog, including license pricing, available download formats (MP3, WAV, AIF), artist information, BPM, key, mood, and complete license terms. Use this after search_catalog or ai_search to get full details before purchasing a license.
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  • Get the top co-occurring words and phrases from TV news clips matching a query — the vocabulary framing a topic on television. Returns the most frequent non-stopword terms from matching clips, with relative frequency scores (0–100, where 100 = the query term itself). Use to understand narrative framing, identify related concepts mentioned alongside a topic, or generate follow-up search terms. TV data spans 2009–October 2024.
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