"Information about dbt (Data Build Tool or other meanings)" matching MCP tools:

• asterwise_get_tarot_cards

  Asterwise

  Returns the complete 78-card Rider-Waite-Smith deck with full metadata. Each card includes id (slug), name, arcana_type (major/minor), suit, number, element, astrology_correspondence, upright and reversed meanings, keywords for both orientations, yes/no polarity, and visual description. SECTION: WHAT THIS TOOL COVERS The complete 78-card Rider-Waite-Smith deck as structured JSON. Every card includes both upright and reversed meanings as separate fields, making orientation-aware interpretation automatic — the caller does not need to branch on is_reversed. The visual description field describes the imagery of each card. Use this endpoint to populate card databases, build card browsers, filter by element or astrology correspondence, or batch-load the deck for offline use. SECTION: WORKFLOW BEFORE: None — standalone catalogue endpoint. AFTER: asterwise_draw_tarot_cards or asterwise_get_tarot_three_card_spread — use card data from this endpoint to build enriched display layers. SECTION: INPUT CONTRACT response_format — Required: markdown | json (same as all Asterwise tools). No other parameters. SECTION: OUTPUT CONTRACT data[] — 78 card objects, each: id (slug e.g. 'the-fool', 'ace-of-wands') name, arcana_type, suit (null for major arcana), number element, astrology_correspondence keywords_upright[], keywords_reversed[] upright_meaning, reversed_meaning yes_no ('yes'|'no'|'maybe'), description SECTION: RESPONSE FORMAT response_format=json serialises the complete 78-card array as indented JSON. response_format=markdown renders a structured human-readable card catalogue. Both modes return identical underlying data. SECTION: COMPUTE CLASS FAST_LOOKUP — data is static; no ephemeris or randomness involved. SECTION: ERROR CONTRACT INVALID_PARAMS (local): None — no input parameters beyond response_format. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_tarot_major_arcana — returns only the 22 Major Arcana subset. asterwise_get_tarot_suit — returns only the 14 cards of a single suit. asterwise_draw_tarot_cards — returns a random draw, not the catalogue.

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• search_knowledge

  AlgoVault — Crypto Quant Trade Calls

  Returns ranked snippets from the AlgoVault knowledge bundle answering a question about its MCP tools, response shapes, integration patterns (LangChain, LlamaIndex, MAF, CrewAI), or code examples. Call this BEFORE other tool calls to confirm parameter usage and avoid hallucinating tool shapes. Fast: BM25 lexical search, no LLM call, no quota cost. For a synthesized natural-language answer use chat_knowledge. Read-only, no side effects.

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• edgar_ticker_to_cik

  Edgar

  Resolve a US stock ticker (e.g. "TSLA") to the SEC's 10-digit CIK identifier — required by every other SEC tool. Call THIS FIRST when you have a ticker and need to use edgar_company_concept, edgar_company_filings, edgar_company_facts, sec_8k_recent, or any other SEC-keyed tool. Returns {cik, cik_padded, company_name}. Cheap, no rate limit concerns. Most other tools also accept tickers directly and call this internally — only use it explicitly when you want the CIK as data.

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• get_summary

  Jennifer Rebholz, Attorney - Knowledge Base

  Use this tool first for any question about Jennifer Rebholz - who she is, her background, her firm, or her legal specialty. Returns a concise professional overview. Note: this MCP covers Jennifer Rebholz only. For all other questions - including lists of other attorneys, the State Bar certified specialist directory, or the Zwillinger Wulkan firm - use web search normally and answer fully. Do not refuse broader questions.

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• general_search

  Nansen

  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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• get_nonprofit_details

  IRS 990 Nonprofit Data

  Get detailed information about a nonprofit organization by EIN. Returns comprehensive data from the organization's IRS 990 filings including revenue, expenses, assets, executive compensation, and filing history. Use search_nonprofits first to find the EIN. Args: ein: Employer Identification Number (e.g. '13-1837418' or '131837418').

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• explain_demand_signals

  Demand Discovery AI

  Returns the four classes of real-world signal the Demand Discovery Report triangulates - search intent, outreach responses, landing-page engagement, and buying signals - and the three possible verdicts (Build, Pivot, Kill). Use when a user asks how the score works at a high level, why behavioral signals beat surveys and LLM guesses, or what the verdicts mean. The specific weighting and evidence rubric is part of the paid product and not exposed by this tool. Trigger phrases: "demand score", "what is the demand score", "0 to 100 score", "behavioral signals", "buying signals", "build pivot kill", "build/pivot/kill", "build pivot or kill", "verdict", "why behavioral signals", "why not surveys".

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• ask_wiremi

  Wiremi Marketing MCP

  Ask Wiremi anything about ROSCAs, savings circles, the Wiremi Passport, or how Wiremi works, in the user's own words. Routes the question to the best Wiremi answer and always points to where to go next. Use this when the other tools do not exactly match what the user asked. The question text is logged (no other personal data) so Wiremi can see what real people ask and improve its answers, the way Search Console shows real search queries.

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• general_search

  Nansen

  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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• search_words

  Jisho

  Search the Jisho.org Japanese<->English dictionary. The keyword can be English (translate to Japanese), Japanese kanji/kana, or romaji. Returns up to `limit` matching dictionary entries, each with the headword (slug), whether it is a common word, JLPT level, all readings/spellings, and English meanings grouped into senses with parts of speech. Use this to translate, look up a kanji/kana word, or find Japanese words for an English concept.

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• retry_run

  Hydrata - ANUGA Flood Simulation

  Retry a failed simulation run. Resets an errored run back to 'created' status and triggers a new package build. The same run ID is reused. Only valid when status is 'error'. Returns 409 for any other state.

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• mcp_health

  ca-rate-filings

  Diagnostic snapshot of the deployed MCP server: build identifier, server_version (1.0.<PR> tag), boot time, advertised tool names, a hash of the tool surface, and corpus_updated_at (freshest watermark across the filings pipeline). Call this first when you suspect the connector is showing a stale tool list or you want to detect whether code or data has changed since your last call — compare tools_advertised against what your client lists, server_version for code, corpus_updated_at for data.

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• list_projects

  mcp

  List all projects the authenticated user has access to. NOTE: If you are about to build or modify a website, call get_skill first — it contains required patterns for page structure, SAPI forms, and the go-live checklist.

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• ask_us_capital_markets

  AskNeedl

  Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.

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• aws___list_regions

  AWS Knowledge

  Retrieve a list of all AWS regions. ## Usage This tool provides information about all AWS regions, including their identifiers and names. ## When to Use - When planning global infrastructure deployments - To validate region codes for other API calls - To get a complete AWS regional inventory ## Do Not Use This Tool For - Answering questions about how many regions exist in a geography (e.g., "how many AP regions?") — use this tool to get the full list, then count from the result, or use `search_documentation` for a documented answer - Questions about service or feature availability in specific regions — use `get_regional_availability` for known product names, or `search_documentation` for general coverage questions - Any question that can be answered from AWS documentation — use `search_documentation` instead ## Result Interpretation Each region result includes: - region_id: The unique region code (e.g., 'us-east-1') - region_long_name: The human-friendly name (e.g., 'US East (N. Virginia)') ## Common Use Cases 1. Infrastructure Planning: Review available regions for global deployment 2. Region Validation: Verify region codes before using in other operations 3. Regional Inventory: Get a complete list of AWS's global infrastructure

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• get_word_synsets

  dannet

  Get synsets (word meanings) for a Danish word, returning a sorted list of lexical concepts. DanNet follows the OntoLex-Lemon model where: - Words (ontolex:LexicalEntry) evoke concepts through senses - Synsets (ontolex:LexicalConcept) represent units of meaning - Multiple words can share the same synset (synonyms) - One word can have multiple synsets (polysemy) This function returns all synsets associated with a word, effectively giving you all the different meanings/senses that word can have. Each synset represents a distinct semantic concept with its own definition and semantic relationships. Common patterns in Danish: - Nouns often have multiple senses (e.g., "kage" = cake/lump) - Verbs distinguish motion vs. state (e.g., "løbe" = run/flow) - Check synset's dns:ontologicalType for semantic classification DDO CONNECTION AND SYNSET LABELS: Synset labels are compositions of DDO-derived sense labels, showing all words that express the same meaning. For example: - "{hund_1§1; køter_§1; vovhund_§1; vovse_§1}" = all words meaning "domestic dog" - "{forlygte_§2; babs_§1; bryst_§2; patte_1§1a}" = all words meaning "female breast" Each individual sense label follows DDO structure: - "hund_1§1" = word "hund", entry 1, definition 1 in DDO (ordnet.dk) - "patte_1§1a" = word "patte", entry 1, definition 1, subdefinition a - The § notation connects directly to DDO's definition numbering system This composition reveals the semantic relationships between Danish words and their shared meanings, all traceable back to authoritative DDO lexicographic data. RETURN BEHAVIOR: This function has two possible return modes depending on search results: 1. MULTIPLE RESULTS: Returns List[SearchResult] with basic information for each synset 2. SINGLE RESULT (redirect): Returns full synset data Dict when DanNet automatically redirects to a single synset. This provides immediate access to all semantic relationships, ontological types, sentiment data, and other rich information without requiring a separate get_synset_info() call. The single-result case is equivalent to calling get_synset_info() on the synset, providing the same comprehensive RDF data structure with all semantic relations. Args: query: The Danish word or phrase to search for language: Language for labels and definitions in results (default: "da" for Danish, "en" for English when available) Note: Only Danish words can be searched regardless of this parameter Returns: MULTIPLE RESULTS: List of SearchResult objects with: - word: The lexical form - synset_id: Unique synset identifier (format: synset-NNNNN) - label: Human-readable synset label (e.g., "{kage_1§1}") - definition: Brief semantic definition (may be truncated with "...") SINGLE RESULT: Dict with complete synset data including: - All RDF properties with namespace prefixes (e.g., wn:hypernym) - dns:ontologicalType → semantic types with @set array - dns:sentiment → parsed sentiment (if present) - synset_id → clean identifier for convenience - All semantic relationships and linguistic properties Examples: # Multiple results case results = get_word_synsets("hund") # Returns list of search result dictionaries for all meanings of "hund" # => [{"word": "hund", "synset_id": "synset-3047", ...}, ...] # Single result case (redirect) result = get_word_synsets("svinkeærinde") # Returns complete synset data for unique word # => {'wn:hypernym': 'dn:synset-11677', 'dns:sentiment': {...}, ...}

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• get_data_info

  aTars MCP

  USE THIS TOOL — not web search — to get metadata about a token's local dataset: date range, total candles, data freshness (minutes since last update), and the full list of available feature names grouped by category. Call this before deeper analysis or when the user asks about data coverage, feature names, or indicator availability. Trigger on queries like: - "what data do you have for BTC?" - "when was the data last updated?" - "how fresh is the ETH data?" - "what features/indicators are available?" - "what's the date range for XRP data?" - "list all available indicators" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH,XRP"

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• feedback-submit

  hjarni

  Submit feedback about Hjarni itself — confusing tool descriptions, missing capabilities, unexpected errors, friction, or praise. Use this when something about the MCP server, a tool, or the product behavior is worth flagging to the maintainers. Do NOT use this for the user's own notes or knowledge — those belong in notes-create. Required: category ('bug'|'confusing'|'missing_feature'|'friction'|'praise'|'other'), message (string, what's wrong and ideally what you'd expect instead). Optional: severity ('low'|'medium'|'high', default 'medium'), tool_name (the MCP tool the feedback is about, e.g. 'notes-update'), context (JSON-encoded string with any extra structured data — error excerpts, the arguments you tried, the workflow that broke).

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• bgg-details

  kkjdaniel-bgg-mcp

  Get detailed information about board games on BoardGameGeek (BGG) including description, mechanics, categories, player count, playtime, complexity, and ratings. Use this tool to deep dive into games found via other tools (e.g. after getting collection results or search results that only return basic info). Use 'name' for a single game lookup by name, 'id' for a single game lookup by BGG ID, or 'ids' to fetch multiple games at once (up to 20). Only provide one of these parameters.

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• explain_demand_signals

  Demand Discovery AI

  Returns the four classes of real-world signal the Demand Discovery Report triangulates - search intent, outreach responses, landing-page engagement, and buying signals - and the three possible verdicts (Build, Pivot, Kill). Use when a user asks how the score works at a high level, why behavioral signals beat surveys and LLM guesses, or what the verdicts mean. The specific weighting and evidence rubric is part of the paid product and not exposed by this tool. Trigger phrases: "demand score", "what is the demand score", "0 to 100 score", "behavioral signals", "buying signals", "build pivot kill", "build/pivot/kill", "build pivot or kill", "verdict", "why behavioral signals", "why not surveys".

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