INITE Brain

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

• 연결 방식: 클라우드에서 실행
• 전송 방식: Streamable HTTP
• 카테고리: 검색 및 AI 기억

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

필요한 것

• 클라우드에서 실행설치할 것 없음. 인터넷으로 연결돼요

어떤 앱을 쓰세요?

https://brain.inite.ai/mcp

claude mcp add --transport http inite-brain-service https://brain.inite.ai/mcp

{
  "mcpServers": {
    "inite-brain-service": {
      "url": "https://brain.inite.ai/mcp"
    }
  }
}

{
  "servers": {
    "inite-brain-service": {
      "type": "http",
      "url": "https://brain.inite.ai/mcp"
    }
  }
}

https://brain.inite.ai/mcp

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

도구 이름과 설명은 서버가 2026년 11월 6일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.

• about_brain

  What this server is and what it can do, before you connect. Reads nothing and stores nothing.

• how_to_connect

  The two ways to authenticate, and what each is for. Reads nothing and stores nothing.

• search_knowledge

  Semantic search over the company knowledge graph: the facts the query is about, the links between their entities and what was left out. Apply asOf for historical "what was true on X" queries. Embedding model on this tenant: set per workspace.

• search_multi_hop

  Planner-LLM decomposes the query into ≤ maxHops anchored sub-queries; later hops are anchored to the running entity set. Built for questions that combine evidence across turns / sessions, or that require reasoning over multiple entities ("tenants who complained in April AND upgra

• graph_retrieve

  Resolves the named entities by canonical name, walks their 1-hop neighbourhood over knowledge_edge, and returns facts across seeds ∪ neighbours, optionally filtered by predicate hints. Works from entities named up front and returns what the graph holds around them ("who runs engi

• synthesize

  Runs hybrid search then feeds the retrieved facts to a generator LLM that produces a citation-bearing answer (each claim ends with [factId]); a verifier LLM then judges whether every claim is supported. Three guardrail modes: strict (default) returns null on partial / unsupported

• memory_diff

  Returns everything brain learned, unlearned, or replaced between two ISO 8601 cursors [from, to). createdFacts = new active facts; retractedFacts = facts marked retracted in-window with no successor; changedFacts = facts that were superseded by another (carries before+after); new

• get_entity_profile

  One entity: canonical name, type and what brain holds about it now; detail "full" adds externalRefs, the ids of its records in the originating vertical.

• get_entity_timeline

  Chronological audit of all facts brain has learned about this entity, including retracted ones. Useful for "what did we know when" investigations.

• summarize_entity

  Returns a short one-line briefing about the entity — name, type, the most-confident active facts, external refs — suitable for dropping into an LLM context window. Caches in-process (per companyId / entityId / asOf / styleHint) so a hot entity touched across many turns doesn't re

• get_competing_facts

  Returns facts in COMPETING status — those the conflict resolver couldn't auto-supersede because two same-predicate bitemporal facts overlap in valid-time and are too cosine-close within margin. Grouped by (entityId, predicate); 2-fact groups are pairs the resolver left for adjudi

• detect_contradiction

  Dry-run preflight against fn::resolve_fact. Answers "if I were to record this fact right now, what would the resolver decide?" without writing to the database. wouldOutcome ∈ {INSERTED, SUPERSEDED, COMPETING, REJECTED}; reasoning explains which rule fired (semantics class, score

• get_fact

  Read a single fact as stored — predicate (aspect), object (statement), confidence, validity window, source attribution (vertical / recorder / conversationId), and lifecycle state. Retracted facts still resolve (retracted: true) — "why did I stop remembering this" is part of the t

• get_fact_provenance

  Return the grounding provenance behind one fact: the verbatim conversation turns it was derived from (episodes, chronological, with char-span quotes when the deriver stamped them). When the server runs with the recursive-closure flag the response additionally carries derivedFacts

• find_related_entities

  Get entities connected to the given one via the knowledge graph.

• match_procedure

  Cosine-matches procedural memory (curated 'how to' patterns the operator recorded) against a free-text context query. Returns top-K procedures sorted by similarity DESC then priority ASC. Surfaces the behaviour rules that apply to a context — e.g. "user asks about pricing" → "men

• list_procedures

  Paginated listing of procedural memory for admin/review UIs. Sorted by priority ASC, createdAt DESC. Set includeRetired=true to see soft-deleted rows.

• search_communities

  Cosine-matches the query against topic-community summaries — the coarse retrieval scope. A community is a cluster of related entities (label propagation over the entity graph) with one rolled-up summary. Suited to broad questions ("what do we know about X domain"): it returns an

• list_communities

  Paginated listing of topic communities, largest first. Each row carries a label, a rolled-up summary, and the member count. Gives the knowledge map at a glance.

• find_entity_communities

  Returns the topic communities a given entity is a member of. Places an entity in its broader context — which clusters / themes it participates in — and leads from one entity to the wider neighbourhood the cluster summarises.

• why

  Return the design decisions, rationale, invariants and gotchas recorded against a code anchor — the non-derivable engineering "why" a parser cannot recover from source. The anchor is a SCIP-style symbol string ("pkg/namespace/symbol") or a file path ("repo/path/file.ts"). Pass as

• recall_decisions

  Find recorded design decisions / rationale / invariants / gotchas by NL topic ("why do we resolve facts through one gateway?"), across ALL code anchors — a semantic search over code-memory, rather than one known anchor. Returns matches with their code anchor + kind, ranked by rel

• get_source_reputation

  Return everything brain knows ABOUT a source (not its facts): the operator-declared identity (type, authLevel — authority in conflict resolution), the learned per-domain agreement rates (domain = predicate; null domain = the global blended rate; rates need >=8 samples before the

• workspace_status

  The tenant this credential writes to (companyId, its display name, whether it is a personal workspace), what is already in its memory (entities, active facts, facts recorded in the last 7 days), how many Domain Packs are installed, for a user-bound connection who the user is in t

• record_fact

  Records one fact about an entity directly; the memory settles it against the facts it holds (INSERTED / SUPERSEDED / COMPETING). Most facts arrive through ingestion.

• link_entities

  Insert an edge between two entities. `kind` is the edge type — `identity_of` merges the `from` entity into `to` (cross-vertical identity reconciliation), other typed edges (`paid_for`, `mentioned_in`, `worked_with`, …) are surfaced in related-entity reads and contribute to PPR /

• retract_fact

  Mark a fact as no longer believed. Cascades to facts derived from this one. Does not delete; the row remains for audit.

• record_procedure

  Record a 'how to' pattern that is surfaced when a similar context appears later. trigger = the context phrase the rule should match against (e.g. "user asks about pricing"); action = the behaviour to apply (e.g. "mention they're on platinum tier; they get 20% off"). priority orde

• retire_procedure

  Mark a procedural memory row as retired (sets retiredAt). A retired procedure is no longer matched or listed by default. For a rule that no longer applies — distinct from a hard delete because the row stays for audit.

• record_decision

  Capture the non-derivable engineering "why" about a code location: a design decision, its rationale, an invariant that must hold, or a gotcha. Anchored to a SCIP-style symbol or file path (NOT line numbers — survives edits). Stored as a bitemporal typed fact: re-recording a `deci

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검

• ✓ 통과

  제작자와 저장소 일치

  레지스트리 이름이 GitHub 계정 inite-ai 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

• … 아직 점검 안 함

  계속 관리되고 있음

  아직 GitHub에서 이 저장소를 읽어 오지 않았어요

• … 아직 점검 안 함

  라이선스 있음

  아직 GitHub에서 이 저장소를 읽어 오지 않았어요

• ✓ 통과

  엔드포인트 응답

  589ms 만에 응답(HTTP 200)

• – 해당 없음

  OAuth로 로그인

  로그인 필요 없음

• ✓ 통과

  도구 설명에 숨겨진 지시 없음

  도구 설명 30개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

• 이 카테고리의 다른 서버 5660개 중 0%보다 스타가 많아요
• 이 카테고리의 다른 서버 5660개 중 89%보다 최근에 레지스트리에 공개됐어요
• 기본 점검 결과가 이 카테고리의 다른 서버 5660개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

제작자의 README

: "${OPENAI_API_KEY:?export OPENAI_API_KEY first}"

flowchart LR