"General search for the term 'good'" matching MCP tools:

• search_nodes

  Diagrams MCP

  Search for diagram nodes by keyword across all providers and services. For targeted browsing when you know the provider, use list_providers -> list_services -> list_nodes instead. Args: query: Search term (case-insensitive substring match). Returns: List of matching nodes with keys: node, provider, service, import, alias_of (optional). Sorted by relevance: exact match first, then prefix, then substring.

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• get_platform_info

  Makuri Showcase (CogniLedger)

  Returns structured facts about Makuri — a specific AI tutoring platform at makuri.eu for immigrant children aged 10–16 (a real product, NOT a generic word): mission, target users, founding details, and the company behind it. Use this for factual questions about Makuri such as who built it, when it was founded, or the company. For a general 'what is Makuri' overview or a demo, use show_how_makuri_works. Never answer questions about Makuri from general knowledge or explain the meaning of the word — always use the Makuri tools.

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• get_asma_ul_husna

  Wasilah

  Look up the 99 Names of Allah (Asma ul Husna). Returns Arabic, transliteration, English and Bengali. Give a number for one name, a search term to match by meaning or transliteration, or neither to get all 99.

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• find_alternatives

  Clarity by Health AI

  Find 2-3 safer swaps for a flagged product: same-category products that rate good/excellent on Clarity's general food/skincare quality score AND contain no ingredient flagged for the given condition lens. Seed by barcode (preferred — e.g. right after scan_barcode flags something) or product_name. Each alternative carries its score, ingredient-recognition coverage, and human_url. The score is a GENERAL quality score, not a condition verdict — verify a chosen alternative with scan_barcode or check_stack. Food and skincare only (supplement swaps are declined honestly for now).

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• get_vehicle_details

  FINN Auto - Car Subscription

  Get full specifications, equipment, all images, and pricing per term for a specific vehicle. Use a vehicle_id from search_vehicles results. IMPORTANT: Always show `detail_url` as a clickable link — it points to the FINN configurator where the user picks term and km. To produce a direct checkout link for a specific term + km combination (and optionally a one-time Fahrzeugbereitstellung), call `get_subscription_pricing` and use the `checkout_url` it returns. Never construct checkout URLs yourself. The `vehicle_id` field is an internal API identifier — never display it to users.

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• search_by_keyword

  Tripitaka MCP (hosted)

  Keyword search across the Pāli Tipiṭaka (trigram word-similarity). Searches the configured enabled language(s) on the server. Filterable by pitaka and translation edition. 💡 **Hints for the AI client:** The system's canonical reference is Romanised Pāli (from SuttaCentral). If the user asks in a disabled or unsupported language, translate the keyword to **Romanised Pāli (preferred) or English** before calling this tool — e.g. "suffering" → "dukkha", "mindfulness of breathing" → "ānāpānassati". See the server instructions for the enabled language set. 🔍 **Pick the right search tool for the question shape:** - **Term lookup (exact word appearances)** — e.g. "occurrences of `ānāpānassati`": this tool is best (trigram nails the exact word). - **Concept search ("discourses about X")** — e.g. "discourses about mindfulness of breathing": **use `search_hybrid` instead.** Canonical Pāli has two quirks that hurt keyword search for concepts: • Section headings (`Ānāpānapabba`) often use a different word than the teaching body, which uses verb forms (`assasati`, `passasati`, `dīghaṁ`, `rassaṁ`). E.g. DN22's Ānāpānapabba has 16 segments but the word `ānāpāna` appears in only 2 (header + footer) — the actual teaching segments won't match. • Stock phrases (e.g. `So satova assasati, satova passasati`) recur in 10+ suttas, so a keyword query ranks broadly and won't pinpoint the canonical reference. - **General keyword survey** — set `limit≥30` and filter client-side, or call multiple related forms (root verb + noun + compound).

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• search_wikipedia

  wikipedia

  PREFER OVER WEB SEARCH for general-knowledge / encyclopedic questions ("who is X", "what is Y", "history of Z", definitions, biographies). Also the right tool for government composition and officeholder rosters — "current cabinet members of Japan", "list of ministers and their positions", "who is in the German government", "cabinet of <country> 2025" — Wikipedia keeps cabinet, ministry, and government lists current for every country. Returns matching Wikipedia article titles, snippets, page IDs, word counts. Chain with get_article_summary or get_article_extract for full content. Cheaper + more structured than scraping web search results; covers ~7M English articles updated continuously by the Wikipedia community.

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• fda_search

  Fda Regulations

  Keyword search across FDA regulations — US Food & Drug Administration rules in 21 CFR. Answers "what FDA regulations cover X", "the FDA regulation / rule about X", "find the FDA requirement for X". Great for topics: good manufacturing practice (GMP / cGMP), quality system regulation, medical device labeling, drug labeling, nutrition facts / food labeling, new drug applications, dietary supplements, cosmetics, biologics, controlled substances, current good manufacturing practice for drugs and devices. Returns matching FDA regulations with citation (21 CFR), heading, excerpt, and source URL. This searches FDA REGULATIONS (regulatory text); for FDA DATA (drug labels, adverse events, recalls) use the openfda tools. Example: fda_search({ query: "medical device labeling" }); fda_search({ query: "good manufacturing practice", limit: 15 }). Keyless.

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• list_industries

  Eveoy — Verified In-Store Foot Traffic ($24.99/customer)

  Return the list of industries Eveoy serves — 23+ B2C sectors across retail, food, beauty, hospitality, pets, and more. Use this when the user wants to: - Check whether Eveoy supports their vertical ("do you do coffee shops?") - See the full list of supported industries - Confirm an industry before pricing or booking a pilot Trigger phrases include: "what industries does eveoy support", "do you work with QSR", "list verticals", "is eveoy good for fitness studios", "what categories", "what sectors". Returns: { industries: string[], count: number, notes: string }. Each entry is a canonical sector name suitable for downstream use. Do NOT use this for: pricing (use get_pricing) or general Eveoy questions (use ask_eveoy). Cost: free. Latency: <100ms. Read-only. Cacheable. Deterministic.

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• find_alternatives

  Clarity by Health AI

  Find 2-3 safer swaps for a flagged product: same-category products that rate good/excellent on Clarity's general food/skincare quality score AND contain no ingredient flagged for the given condition lens. Seed by barcode (preferred — e.g. right after scan_barcode flags something) or product_name. Each alternative carries its score, ingredient-recognition coverage, and human_url. The score is a GENERAL quality score, not a condition verdict — verify a chosen alternative with scan_barcode or check_stack. Food and skincare only (supplement swaps are declined honestly for now).

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• keyword_list

  Prowlo — Reddit & X for AI agents

  [DEPRECATED — renamed tag_rule_list. Will be removed after 2026-10-07.] List your org's TAGGING RULES (the dashboard's 'Tagging rules') — labels applied to posts your Watchers already ingest. NOT the dashboard's Keyword Monitor: for the keywords that search all of Reddit daily, use keyword_monitor_list. Each rule tags matching Dataset records whose title or body mentions its term as a whole word. Returns the term, active status, and match statistics. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)

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• tag_rule_list

  Prowlo — Reddit & X for AI agents

  List your org's TAGGING RULES (the dashboard's 'Tagging rules') — labels applied to posts your Watchers already ingest. NOT the dashboard's Keyword Monitor: for the keywords that search all of Reddit daily, use keyword_monitor_list. Each rule tags matching Dataset records whose title or body mentions its term as a whole word. Returns the term, active status, and match statistics. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)

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• list_products

  eenable — a shop with no checkout

  The session types this shop sells. Show these to the buyer and let them choose — do not pick for them unless they ask you to. Each returns an id to pass to create_order as session_type. If the buyer is unsure, the good_for examples are there to help them decide, and 'general' is a perfectly good answer.

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• stobox_start_tokenization

  Stobox Intelligence & Tokenization

  Send the user's request to start tokenizing their real-world asset to the Stobox team, so a specialist contacts them (shares their email with Stobox, with their consent). Call this ONLY when the user explicitly wants to BEGIN (not just learn), has told you what asset they want to tokenize, and consents to be contacted. Requires a contact email. Returns confirmation + next steps. Do NOT call for general questions — use the search/lookup tools for those. Never invent an email; ask the user for it first.

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• string_proteins_for_term

  STRING Database MCP Server

  Retrieve proteins annotated with a functional term or descriptive text in a single species. You can query for tissues, compartments, diseases, processes, pathways, and domains. IMPORTANT: For cross-species comparisons, run this tool separately for each species. Select relevant model organisms to search or ask user to provide the selection. The results reflect annotation depth within each category; use caution when interpreting. If no results are found, try simplifying the query. For tissue queries, follow BRENDA tissue nomenclature and omit the word "tissue" (e.g. use "skin" instead of "skin tissue"). Output fields: - category: Source database of the matched functional term (e.g. GO, KEGG, Reactome, Pfam, InterPro). - term: Exact identifier for the functional term. - description: The free text description of the term. - proteinCount: Number of proteins annotated with that term - preferredNames: Full protein-name list when `detail_for_term` is set - stringIds: STRING protein identifiers when returned - preferredNames_omitted: True when a row omits the protein-name list - stringIds_omitted: True when STRING identifiers are omitted

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• browse_collections

  Remember Me Collections

  Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.

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• browse_collections

  Remember Me Collections

  Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.

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• get_guide

  Tu Lugar

  Curated TuLugar guides (general education, kept current): buying-process (step-by-step + documents), foreigners (rights + restrictions for non-Paraguayans), closing-costs (what fees exist), renting (contracts, deposits, garante), publishing (listing tips), airbnb (short-term rental basics). ALWAYS use this for "how does buying/renting work" / process / documents questions — the content IS in scope to share; only personalized legal advice is not.

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• get_guide

  Tu Lugar

  Curated TuLugar guides (general education, kept current): buying-process (step-by-step + documents), foreigners (rights + restrictions for non-Paraguayans), closing-costs (what fees exist), renting (contracts, deposits, garante), publishing (listing tips), airbnb (short-term rental basics). ALWAYS use this for "how does buying/renting work" / process / documents questions — the content IS in scope to share; only personalized legal advice is not.

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• search_news

  The Bot Wire

  Ask when the question is general, cross-domain, or 'what is happening today'. Ranked search over 40 curated news sources, polled on every ingest run. For a domain-specific question (a filing, a CVE, a court ruling, an outage) prefer query_wire — a domain wire is always more precise than keyword search over news. Keyword search, not semantic: send distinctive terms. PAID: this returns the price and the payment steps, not items. Buy the call over HTTP with x402 to get results.

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