"Understanding the concept of 'handle' in different contexts" matching MCP tools:

• find_equivalent

  Medical Terminologies MCP

  Ranked unified search for equivalent terms across multiple medical terminologies. Use this tool to: - Find the same concept in different coding systems - Compare how terminologies represent a concept - Support terminology mapping and data integration Searches across: ICD-11, SNOMED CT, LOINC, RxNorm, and MeSH. Set `target_terminologies` to limit which are searched, or set `source_terminology` to exclude one (e.g. when you already have a code from that terminology and want equivalents elsewhere). The two combine: source is subtracted from targets. `limit` caps candidates per terminology (default 5, max 10). Every candidate carries `match_score` (lexical similarity to the search term, 0-1) and `rank` (global position across all searched terminologies) — both computed by this server, since upstreams don't expose comparable relevance scores. Candidates from different terminologies whose titles are lexically identical are clustered in `groups` — a strong same-concept signal (absence of a group is NOT evidence of non-equivalence). Searches upstreams in English. For official pt-BR content, use the dedicated tools: `icd11_search`/`mesh_search` accept `language: "pt"`, and `cid10_search` is natively Portuguese.

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• search

  Islam West Africa Collection (IWAC)

  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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• create_cart

  Kifly — Agentic Commerce & Payments

  Create a new shopping cart on Kifly. **For network (cross-seller) tokens you MUST pass `seller_handle`** — each cart is bound to exactly one seller. Get the handle from search_products results (every item's `kifly:seller` IS the handle in network results) or get_seller. Seller-scoped tokens may omit the handle — their own seller is implicit. Returns a cart_id to use with add_to_cart and checkout. The response's `seller.kifly_purchasable` (and `seller.fulfillment`) tells you upfront whether this seller can complete a real Kifly checkout — `false`/`"external"` means directory-tier: checkout will hand off to the seller's own site instead of charging, so present the flow as a referral, not a purchase. Cart-building still works either way (needed to generate the handoff's per-product links), and the same flag rides every add_to_cart/get_cart response on this cart too.

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• whoami

  shiply

  Who am I? Returns the signed-in account: email, @handle, plan + limits, counts of sites/domains/drives, and connected DNS providers. Call this first to orient before managing sites or domains.

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• beoordeel_tekst

  NeoDemos

  Eén deterministische review-tool voor concept-teksten van een raadslid/fractiemedewerker. Geen LLM, geen DB, <10ms. Kies de modus via `soort`: - `vragen` — scherpt concept schriftelijke/mondelinge vragen aan: flagt suggestief/sturend, meervoudig, gesloten ja/nee, vage kwantoren, en ongefundeerde vragen + 'scherper'-suggestie. - `notitie` / `commissienotitie` / `fractienotitie` — sanity-review (maximaal 10 opmerkingen): ontbrekend voor/tegen-eindoordeel, strategische opstelling, bronnen zonder paginanummer, ontbrekende samenvatting/vragen/bolletjes en suggestieve vragen — gegroepeerd op ernst (hoog/midden/laag). - `spreektekst` — rubriek met cijfer (1-10) + deelscores + verbeterpunten + duur-vs-spreektijd (opening, standpunt, onderbouwing, weerlegging, oproep, lengte ~130 wpm). - RvO-format check: `motie` | `motie_vreemd` | `amendement` | `schriftelijke_vragen` | `mondelinge_vragen` | `initiatiefvoorstel` | `interpellatieverzoek` — valideert structuur + RvO-regels (ontbrekend dictum, geen raadsvoorstel-ref bij amendement, gesloten vragen bij schriftelijke vragen, etc.). Gebruik dit na `genereer_raadsstuk` of op een handgeschreven concept. Gebruik wanneer: het raadslid een concept heeft geschreven en wil weten wat scherper kan. NIET om corpus te doorzoeken → `zoek_raadshistorie`. Retourneert: markdown met concrete verbeterpunten passend bij `soort`, gegroepeerd op ernst. **Positie in de drafting-keten:** roep aan ná `genereer_raadsstuk`; verwerk de bevindingen in het concept en sla daarna op met `sla_fractie_artifact_op(artifact_type=<doc_type>)`.

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• genereer_raadsstuk

  NeoDemos

  Genereert een volledig opgemaakt, RvO-conformant concept voor één van de zeven raadsstuk­typen. Geen DB, geen netwerk, <10ms — puur structurele kennis. Gebruik deze tool wanneer: - Het raadslid een stuk wil indienen en een correct gestructureerd concept nodig heeft. - Je `adviseer_raadsinstrument` hebt gebruikt (welk instrument) en nu het daadwerkelijke stuk wilt renderen in het juiste format met RvO-verwijzingen. - Een concept al bestaat maar opnieuw in correct format moet worden gezet. Gebruik deze tool NIET wanneer: - Je het juiste instrument nog moet kiezen → gebruik eerst `adviseer_raadsinstrument`. - Je een bestaand concept wilt beoordelen op inhoud → `beoordeel_tekst`. - Je een format-validatie wil uitvoeren op een bestaand concept → `beoordeel_tekst` met `soort` gelijk aan het doc_type. ``doc_type`` keuzes: 'motie', 'motie_vreemd', 'amendement', 'schriftelijke_vragen', 'mondelinge_vragen', 'initiatiefvoorstel', 'interpellatieverzoek'. ``velden`` zijn optioneel — ontbrekende velden worden vervangen door invul-placeholders [zoals dit] zodat het concept altijd een compleet, geldig skelet is. ``gemeente`` bepaalt welk lokaal RvO-overlay (artikel­nummers, termijnen, indienings­route) wordt gebruikt. Default 'rotterdam'. Degradeert netjes naar het canonieke basis­format + disclaimer als er geen overlay beschikbaar is. Retourneert: markdown-concept in de juiste RvO-structuur, met RvO-artikel­citaat en disclaimer. **Volgende stap in de drafting-keten:** valideer het gegenereerde concept met `beoordeel_tekst(tekst=<concept>, soort=<doc_type>)` voordat je het presenteert of opslaat; sla daarna op met `sla_fractie_artifact_op(artifact_type=<doc_type>)`.

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• lookup_profiles

  Influship

  Batch-fetch up to 100 profiles by (platform, username) pairs. Use this when the user has a list of handles and you need profile data for all of them at once (e.g., "give me follower counts for these 30 accounts I'm considering" or "which of @a @b @c are real accounts?"). One round-trip beats 30 calls to `get_profile`. Use this for exact batch handle lookup, not semantic discovery. For one exact platform+username pair, use `get_profile`. For partial or fuzzy handle/name input, use `search_creators` or `autocomplete_creators`. Use `semantic_search_creators` only for topical/niche/audience discovery where false-positive semantic matches are acceptable. Examples: - User: "Compare @a, @b, and @c on Instagram" -> use this tool for the exact handle batch. - User: "Give me follower counts for these 30 accounts" -> use this tool. - User: "Find wellness creators in Austin" -> use `semantic_search_creators`, not this tool. The response splits results into `data` (profiles found) and `not_found` (the (platform, username) pairs that weren't recognized). Profiles are returned in no particular order — re-correlate via the platform/username fields if you need to preserve input order.

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• pscale_play

  bsp-mcp

  Inhabit a handle in a world, in one call — the no-fiddle entry that makes 'play anya on thornwood' just work. Resolves the world to its beach (a sub-domain <world>.beach.<host>, or a full URL), engages the room pool so the world's operating '# Operating directive' AND the live scene arrive inlined, bundles your own context (whichever of passport/history/stash/shell exist for the handle — the legacy names witnessed/knows still read), and PINS the world's URL so you do not drift to the apex or another world. Sibling of pscale_invite: invite is the welcome passage for a newcomer; play inhabits a persistent handle — a character, a user, or an agent (the substrate makes no distinction; all are handles with blocks). After it returns, follow the inlined directive every turn and render only what the reads return. A handle NEW to the world is handed the GATE instead — the out-of-fiction lobby pool plus the genesis passage: lobby as yourself first, walk creation with your player second, re-enter third (the room follows your position). Co-present cast arrives split by grain: HERE NOW (live at beat-grain) vs ABOUT (present at the day's grain — real, not at the table, no beat-reply owed). RPG: pscale_play(world='thornwood', handle='anya') → you are Anya in the Beaten Drum, directive and scene in hand.

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• survey_corpus

  Tripitaka MCP (hosted)

  Exhaustively survey the WHOLE Tipiṭaka for a term — guaranteed complete. Use this (not `search_by_keyword`) when the question is about **coverage or counting** rather than "show me the best passages": - "How many times does Kusinārā appear in the canon?" - "Every place ānāpānassati is mentioned — don't miss any" - "Which pitakas/how many suttas mention this term?" Unlike `search_by_keyword` (ranked, capped at 50, no total), this returns an **exact count**, a **per-pitaka breakdown**, the **distinct surface forms** that matched (so you can audit and discard over-matches), and a paginated enumeration. The `lexical` result carries `complete: true` — a hard guarantee that nothing was dropped for the chosen `match_scope`. Two layers, two different promises: - **lexical** — the word and its forms. Deterministic + EXHAUSTIVE. - **semantic** (`mode="thorough"`, hosted only) — passages teaching the same concept with DIFFERENT vocabulary (e.g. ānāpānassati via `assasati`/`passasati`). Approximate, **NOT exhaustive** — it never claims completeness, it only boosts recall.

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• search_hybrid

  Tripitaka MCP (hosted)

  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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• secedgar_get_snapshot

  secedgar-mcp-server

  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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• bsky_search_actors

  bluesky-mcp-server

  Find Bluesky accounts by name or handle fragment. Returns ranked profiles with handle, DID, displayName, bio, pronouns when the account set them, and follower count — but not website, which only bsky_get_profile returns. Use before bsky_get_profile or bsky_get_author_feed when you have a name but not a confirmed handle. Supports cursor-based pagination for browsing beyond the first page of results.

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• describe_services

  Venture Insights Concept Diagnostic

  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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• cart.updateLineQuantity

  droplinked

  Change the quantity of an existing line in a droplinked cart. Identifies the line by skuId (the variant id used when the line was added). Returns `{ status, cartId, skuId, updatedQuantity }`. Use cart.removeLine to remove a line entirely instead of setting quantity=0. Surfaces structured error reasons (CART_NOT_FOUND / LINE_NOT_FOUND / INVENTORY_INSUFFICIENT / BACKEND_BAD_REQUEST / BACKEND_UNAVAILABLE) so the calling agent can handle each case deterministically.

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• shared_context

  UseMyContext

  List and read curated personal context shared with you. With no arguments, lists who shared what (names + ids only, no content). With a `from` selector (a grantId from that list), returns that person's shared profile text. SAVED BY NAME: if the user has saved a context under a short name, pass `saved` (that exact name) to pull it - the service resolves the name to the real source (a share, a teammate, a @handle, or one of the user's own projects) and re-checks access live every time. If that access is gone (revoked, expired, left the team, or closed), it returns a calm "no longer available" note instead of an error. NETWORK: if you already know a member's project @handle, pass `handle` to pull the context they have opened to the UseMyContext network - their live composite, read-only. Each @handle addresses ONE specific project, so the handle alone identifies what to read. ORGANISATION: if you and another person are members of the same UseMyContext team/organisation on an active team plan, pass `org` (the organisation id) and `member` (that teammate's member id) to read their live composite - their curated context only, never their files or facts. There is no directory or browse; you must already know the saved name / handle / org + member ids. Read-only; always allowed; you only ever see what was shared with you, saved by you, opened to the network, or a teammate's context within your own organisation.

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• find_similar_creatives

  CreativeScope — Mobile Game Ad Creative Intelligence

  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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• update_profile

  Tenjin

  Create or update your publisher profile — the byline and price default every piece you publish inherits. Only the fields you send change; everything else keeps its stored value. Claiming a `handle` moves your public URLs off your 0x address (/c/<handle>, /a/<handle>/<slug>), and RENAMING releases the old handle: its URLs stop resolving at once, and after a 90-day cooldown anyone may claim it — so pick once. Sending `displayName` while you hold no handle auto-claims one from it when that handle is free; the outcome, claimed or not, comes back in the warnings. PUT /api/me stays the sole validator; this tool forwards your fields verbatim. Read the stored result back with get_profile, or as other agents see it with get_creator. Mint a FRESH SIGN-IN-WITH-X for this call: the write routes burn each nonce once, so a header you already spent is rejected.

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• ic_funko_set_public

  Immersive Commons

  Flip the caller's OWN publicShare switch. TRUE makes their handle, display name, figure parts, unlock set and member stats readable by ANY agent on the internet with no token (via ic_funko_get or a plain GET of /api/funko/m/<handle>); FALSE takes it back, and the endpoint immediately returns the same not_found as an unregistered handle. Default is FALSE — a member is private until they say otherwise, so confirm with your human before turning this on. Reversible either way. Targets the caller's own profile ONLY; there is no argument that names another member. Args: { public_share: boolean }. Returns: { ok, handle, public_share, profile_url }. Required scope: funko:write (ic-member+; live tier re-checked at call time).

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• entity_lookup

  The Chancery Lane Project

  Find TCLP content nodes (clauses, glossary terms) associated with a named concept. Unlike `search`, this performs a deterministic name match against Entity nodes in the knowledge graph rather than a relevance-ranked semantic search. Use it when you have a specific term or concept (e.g. "scope 3 emissions", "net zero") and want to retrieve every clause or glossary entry that explicitly references it. Args: name: The entity or concept name to look up (exact match, case-insensitive). limit: Maximum number of results to return (1–50). include_full_text: Include each hit's full body text (Markdown). Off by default — bodies are large; request only when you need the content, and prefer a small `limit` when you do. Returns: JSON with "meta" and "results" where each hit includes the source content node and the entity names that matched.

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• pscale_key_publish

  bsp-mcp

  Derive an X25519+Ed25519 keypair from your secret + handle (Argon2id). Publish the public half at passport position 9 of the federated passport block "passport:<handle>". Private half is never stored. Same secret + handle always produces the same keys. Passport block must exist at the beach first. Rotation requires proof of prior key ownership (prior_secret OR signature). Defaults to https://beach.happyseaurchin.com; pass agent_id to publish at a different beach.

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