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511,937 tools. Updated 2026-09-04 15:44

"A search about the concept and practice of magic" matching MCP tools:

  • Browse and filter the healthcare vendor directory. Use this for open-ended exploration, e.g. "show me medical billing companies in Texas", "list credentialing services", "what EHR vendors are there for cardiology", or when the user wants to page through options rather than get a scored shortlist. Paginated results filtered by category, location, minimum quality score, curated Tier-1 grade, and practice-size fit; returns a page of providers with {company_name, category, city, state_abbr, quality_score (0-100), verified status, contact info, slug}. For a scored recommendation to a specific practice profile, use match_practice instead. Pass a returned slug to get_provider_detail for the full profile.
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  • Find US medical codes whose official descriptions match a described concept, via full-text search over the bundled index. Every search term must appear — matched first as a token prefix, then as a substring so inflected and compound forms are also found (a "neuropathy" search surfaces "mononeuropathy"/"polyneuropathy" siblings too, not only a standalone "neuropathy" token). Filter by `system` (ICD10CM/ICD10PCS/HCPCS/RXNORM), `billableOnly` to exclude headers/categories, and `chapter`. Use when you have a clinical description and need the code — the reverse of medcode_get_code. Results echo the resolved system per row for chaining, rank exact prefix matches ahead of substring-only matches with a deterministic tie-break, and disclose truncation with a `nextCursor`: pass it back as `cursor` to page through the full ranked set.
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  • Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, audiovisual recordings, photographs, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every word to appear somewhere in the item, so prefer a single concept per call. Write query strings and concept keywords in French for press/publication/document/index discovery even when the user's report language is not French. Academic references are multilingual, so try French and English title/abstract terms when relevant; metadata/filter labels remain French. Use the French transliteration of Islamic terms (Tabaski not 'Eid al-Adha', charia not 'sharia', Maouloud not 'Mawlid'). Returns {results:[{id,title,url,category}], ranking}; each result's `category` names its subset and the `ranking` field documents the ordering. Pass an id to `fetch` to read the full text. For filtered queries (by country, date, or newspaper) use the search_* tools instead.
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  • Search US SEC 8-K and 6-K current-report nodes for company events and disclosures. Use this to discover issuers across a date range. Do not use this for 10-K or 10-Q filings. How to search: 1. Always pass concept_groups. Every group is required (AND). Within each group's any_of list, one alternative must match (OR). All groups match inside one filing node. Use separate groups for the main context, action or direction, business object or metric, and a causal or limiting relation when that relation is essential. 2. Optionally pass query with likely verbatim disclosure phrases. Each item is an exact adjacent-token phrase. Put alternate full phrasings in the same list. Query plus concept_groups is hybrid search: exact phrase matches receive a score boost, and concept groups recover different wording. Do not put broad topic words such as "China", "AI", "customer", or "restructuring" alone in query. 3. Add real synonyms and alternate filing language to any_of. The concept path uses English stemming, so one base form usually covers inflections (decline/declined/declining and volume/volumes). Stemming does not add synonyms (sales does not mean revenue; reduce does not mean weaken). 4. Do not search with query only. Omit query for concept-only search. If query is omitted, the search is concept-only. 5. Use date filters for time and tickers to search only selected issuers. Pass ne_tickers (or prefix a symbol with !) to omit issuers. 6. Results are candidates, not final conclusions. Call read_node_content with each promising document_id and node_id(s). Verify negation, causal claims, comparisons across periods, and numeric thresholds such as a percentage or dollar amount in the source text. Cite CITATION_MARKDOWN. When you finish an issuer, search again with the same inputs and add its ticker to ne_tickers so later hits come from other issuers. Examples of useful group dimensions include geography + weakening signal + demand metric; CapEx + reduction + guidance; AI/automation + enablement + workforce + reduction; customer + loss/concentration; data centers + exposure + monetization; or restructuring + program/charge. Do not add a group for a detail that the filing may leave implicit, because every group is mandatory. Each result is one filing node: document_id, node_id, parent_node_id, ticker, type, filing_date, match_mode, query, score, and a short snippet.
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  • 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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  • Hybrid search — combines keyword + semantic search via RRF. Uses Reciprocal Rank Fusion (RRF) to merge exact-word results with meaning-based results. **This is the recommended tool for "discourses about X" / concept queries**, because the semantic side catches suttas that discuss a concept using different vocabulary (e.g. some mindfulness-of-breathing suttas use `assasati/passasati/dīghaṁ` instead of `ānāpānassati`). 💡 **Hints for the AI client:** - English queries usually work best (e.g. `mindfulness of breathing`) because the embedding model is multilingual but EN-primary. - Thai stop-word handling is weak. If a Thai query underperforms, the AI client should translate to Pāli/English first (see server instructions). - The default `limit=5` is often too small for a topic survey — use `limit=15-20` (max 20) for good coverage. - Ranking is by similarity, NOT canonical importance — locus classicus suttas (e.g. MN118, DN22) may rank below smaller suttas that happen to use the exact vocabulary. Treat results as a starting point, then call `get_sutta` for the canonical references.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables LLMs to perform conceptual search over local PDF/EPUB documents using a RAG pipeline with corpus-driven concept extraction and WordNet enrichment.
    3
    MIT
  • F
    license
    A
    quality
    C
    maintenance
    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
    6

Matching MCP Connectors

  • Create and edit images, videos, and audio through Magic Hour's hosted Streamable HTTP MCP server.

  • Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.

  • 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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  • Get Venture Insights' live service catalogue: the FREE Concept Diagnostic (a research-backed viability study of one venture concept, delivered to the founder's inbox) and the paid study tiers with live SAR prices. Call this first when your user asks what Venture Insights offers, what it costs, or whether the free diagnostic is worth requesting.
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  • Rank published articles for a query and return them with titles and URLs. Use when you want sources to read rather than a single answer. Search is sense-aware: bare MSO promotes only the Hong Kong Money Service Operator owner, professional-industry context promotes the regulated-practice platform, and genuinely conflicting context returns both with an explicit interpretation object.
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  • Search only the cards the user OWNS, by name, colors, or type. Set notInDecks to surface owned cards not currently used in any of their decks (the "what is sitting idle in my binder" question). Use search_cards instead to search every Magic card regardless of ownership. Returns at most 100 owned cards per call, with the full match count in `total`. Requires a free API key (send it as "X-API-Key: <key>" or "Authorization: Bearer <key>").
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  • Cast one spell. Name it by id ("light_healing") or by its incantation ("exura") — both work. Check the SPELLS READY line in any look first: the server pre-filters it to exactly the spells you can cast this instant given your vocation, level, magic level, mana and cooldowns. If a spell is not on that line, casting it will be rejected. The full catalogue is the resource golemreach://spells. Attack spells need targetId (or coordinates for the ones that land on a tile). Healing and support spells usually need nothing. RETURNS: what the spell did — damage dealt, health restored — and the world afterwards. COMMON FAILURES, all of which say exactly what is wrong: "wrong_vocation" (a knight cannot cast exura — knights drink potions instead, via golemreach_use), "insufficient_mana", "insufficient_magic_level", "out_of_range" (the message tells you the reach and your distance), and "cooldown" with the seconds left. Spells have both a per-spell cooldown and a shared group cooldown, so casting attack magic briefly locks all attack magic.
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  • Search Vectree's library of ~95,000 interactive concept diagrams by meaning, not keywords. Vectree explains how things work as zoomable, labelled schematics — each diagram breaks a topic into nodes you can read or drill into. Use this when the user wants a diagram, a visual explanation, a systems overview, or a map of how the parts of something fit together. Describe the topic in natural language; the search is semantic, so a full question works better than a bare keyword. Results are ranked by how closely they match and by the quality of the model that generated them. Each result carries a slug — pass it to `get_diagram` for the full content of one diagram. Only public, already-generated diagrams are searched. Nothing is generated on demand, so a topic with no match simply has no diagram yet.
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  • Find visually similar creatives using the stored vector of an existing creative. For a concept without an ID, query selects an explainable seed from available creative metadata and then uses the same vector-neighbor search. For an English concept, send the original English terms only. The service resolves Chinese source-label equivalents internally before selecting the seed. Returns creative records ordered from most to least visually similar; low-similarity and near-duplicate results are excluded, and raw similarity scores are not exposed. If request_echo.seed_basis identifies a proxy seed, clearly disclose that limitation instead of presenting the results as an exact concept match. Example: 'Show variants of the toilet run viral creative concept.'
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  • Search every element type's fields for `query` (case-insensitive substring), across all 22 types. Useful for "which types have a `location` field?" or finding where a concept lives in the schema. Returns a mapping of type slug -> the matching field names in that type (types with no match are omitted); a `query` that also matches a type slug lists that type with an empty field list so the type-name hit is not lost. Unauthenticated.
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  • Search the SAP analytics concept encyclopaedia — the vocabulary of the stack, written for practitioners. Returns slug, title, category, level, tags and the editor's summary. `level` is SPARSE — null on 108 of the 330 active rows, measured 2026-08-27 — and a null there means 'not graded', never 'Beginner'. These are the same fields `get_concept` returns for ONE slug. The card BODY (why-it-matters, key points, cheat sheet, the four analysis tables) is Consultant-tier: call `get_concept_card`.
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  • Build a company financial profile in one call: the latest value of every supported XBRL concept, grouped by statement. Reads the filer's complete companyfacts payload once rather than one request per concept, so it replaces a run of secedgar_get_financials calls when the question is "what do this company's financials look like right now". Values use the same frame dedup and tag priority as secedgar_get_financials, so the two agree for any concept they both cover. Duration concepts (income statement, cash flow, per-share) report their latest full year and latest single quarter; balance-sheet and entity-info concepts report their latest point-in-time value, since that is the only form they are filed in. A concept the filer does not report is listed under gaps with the XBRL tags that were tried — never zero-filled or interpolated. Use secedgar_get_financials for a full time series of one concept, and secedgar_compare_companies to put several companies side by side.
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  • Count Magic Reach opt-outs for a managed community. Before offering this action or requesting its inputs, check business permissions. FREE businesses cannot use this tool, regardless of individual feature rows. Call check_business_tool_access before collecting inputs. Show any grace-period warning and verified resubscribe link before continuing, and never proceed when access is blocked.
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  • Answer a question by quoting a published wiki article. The answer is extracted verbatim, never generated, and always carries the URL it came from. Returns confident=false with suggested reading when the corpus does not cover the question or when context genuinely conflicts. Bare MSO means the Hong Kong Money Service Operator licence; use Management Services Organization or regulated-practice context for the broader platform concept. Ask in the language you want answered — Russian and English are both first-class.
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  • The paid intelligence profile of a services firm — SAP practice size and partner level, delivery flags per product, typical day rate and seniority, notable clients, analytics practice summary, and a LinkedIn company URL (present on ~39% of the corpus — glassdoor_rating, glassdoor_reviews_count and linkedin_followers are null on the entire corpus as of 2026-08-10, absence here is a data gap, not a signal). READ THE SPARSITY BEFORE QUOTING A ROW: on the 9,103 profiles measured 2026-08-23, `typical_day_rate_eur` is null on 78.0% and `sap_partner_level` on 85.7% — the two headline fields are the exception, not the rule, and a null means 'not researched', never 'no partner level'. Requires a subscriber API key, Legend tier or above. Person-shaped fields (contacts, founders, leadership, recruiters, postal addresses) are NEVER served by this endpoint at any tier — they remain behind the platform's signed-URL path. Search by name; the public directory (search_firms) is a different, wider population.
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  • Non-destructive dry run of ownership verification for a toolfound submission: reports, per method, what the checker sees RIGHT NOW — meta tag found or not (with the exact expected tag), DNS TXT found or not (with the exact expected record), and whether the submission email qualifies for the magic-link path. Use it to distinguish 'my deploy is not live yet' from 'wrong token' before calling toolfound_verify_submission. Changes nothing.
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