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MCP Assist — Coordination Memory

제작자: aliomraniH버전 0.4.1i★ –i클라우드에서 실행
레지스트리 이름io.github.aliomraniH/mcp-assist-memory

설치

개요

제작자가 쓴 설명(영어 원문)

Coordination memory with verification: reconcile-against-GitHub, verdict freshness, provenance.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

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
  • 입력해야 할 값: Authorization

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.

필요한 것

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.

터미널에서 이 명령어를 실행하세요

claude mcp add --transport http assist-memory https://mcp-assist-memory.replit.app/mcp --header 'Authorization: your-value'

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "assist-memory": {
      "url": "https://mcp-assist-memory.replit.app/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "assist-memory": {
      "type": "http",
      "url": "https://mcp-assist-memory.replit.app/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

  • Authorization 비밀 필수 HTTP header
    Bearer — operator-issued per-surface token; all MCP access requires it

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

할 수 있는 일

아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.

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 aliomraniH 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

  • … 아직 점검 안 함

    엔드포인트 응답

    아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요

  • … 아직 점검 안 함

    OAuth로 로그인

    아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 7286개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 7286개 중 29%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 7286개 중 100%와 같거나 더 좋아요

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

자주 묻는 질문

MCP Assist — Coordination Memory, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

입력해야 할 값: Authorization

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.4.1)은 3개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Context7, Codebase Memory, Exa

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

Context7

제작자: upstash

Up-to-date docs for AI agents

컴퓨터 또는 클라우드★ 64,224MIT어제 업데이트
설치

Codebase Memory

제작자: DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

내 컴퓨터에서 실행★ 48,148MIT21일 전 업데이트
설치

Exa

제작자: exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

클라우드에서 실행★ 5,213MIT지난달 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

mcp-assist-memory

A generic, project-agnostic memory / coordination / artifact server for multi-agent and multi-surface work. One FastAPI process serves a 30-tool MCP over Streamable HTTP, backed by Postgres (+ pgvector), deployed standalone on a Replit Reserved VM.

This is Tier 1 of the reusability contract: every project reuses it as-is. It carries zero domain terms — project identity lives in namespace *values*, never in tool names, tables, columns, or code.

Capabilities at a glance
  • 30-tool MCP over Streamable HTTP (memory, handoff, session, artifact, coordination, feedback, admin).
  • Trust-boundary spine (Plan v2) — actor-scoped exactly-once writes with visible dedup, read-back-verified acks (verified_persisted), standardized error payloads with remedies, write-time screening + quarantine, provenance tiers (origin, model attribution, derived_from lineage), trust decay (needs_reverification), PHI-safe tool_events telemetry, per-namespace variant profiles, and an observation_log feedback channel.
  • Namespace-scoped multi-tenancy — every per-project query filters on namespace.
  • Resilient to transient DB drops — the server transparently retries genuine connection losses (Neon scale-down / PgBouncer recycle, SQLSTATE 57P01/08xxx) on a fresh pooled connection, and validates connections at checkout, so callers no longer have to retry. Retries are idempotency-gated, so they never double-write.
  • Prompt-injection resistance layer — values are sanitized on write (forged markers are escaped one-way to [[UNTRUSTED_DATA]], never reconstructed on read), instruction-shaped writes are screened and quarantined (visible in the write ack; include_quarantined: true opts reads back in), and reads come back wrapped in << >> markers; storage.sanitize.unwrap_value recovers the raw value when a consumer needs it (e.g. to json.loads). Honest framing: these are layers, not proofs — deterministic screens and wrappers are bypassable by an adaptive attacker; adversarial evaluation is pending (see Phase 10 backlog in DECISION-PROTOCOL.md).
  • Content-addressed artifacts (sha256, global dedup), 50 MB cap, ranged reads.
  • Per-surface rotatable tokens (web vs. desktop-cli) managed from a password-gated /admin dashboard.

The 30 tools

GroupTools
memorymemory_save memory_get memory_list memory_history memory_delete memory_search
handoffhandoff_save handoff_load handoff_list
sessionsession_create session_append_event session_get session_list session_events
artifactartifact_put artifact_get artifact_list
coordinationcoord_health coord_drift_scan coord_reconcile coord_curate
gateintent_open skill_define gate_close_outcome gate_cache_status
sequencesession_bootstrap namespace_init recall
feedbackobservation_log
adminstats

Sequences are the paths an agent should take. Correct use of this server has always been a *sequence* — learn which database answered, resolve the profile, check what is stale, then act — and that ordering used to live in tool descriptions and skills, i.e. it was enforced by a model remembering advice mid-task, and a skipped step produced no signal whatsoever. The three sequence tools run their steps server-side in a fixed order and return steps_run, so the ordering is something the server did rather than something a caller got right. They are strictly additive: every primitive they are built from still works exactly as before, for surgical use.

recall and memory_search now share ONE retrieval guard (storage/retrieval.py): the same absolute floor and relative alpha the Intent Gate applies. Previously memory_search had no floor at all while intent_open had both, so the same store answered the same question differently depending on which tool the caller reached for. They still differ in what they do with the verdict — memory_search annotates every row and drops nothing, recall filters by default and reports the rejected counts — but they can no longer disagree about what counts as a match.

The Intent Gate (claude/intent-gate/INTENT_GATE_CHARTER.md) is a per-namespace opt-in (variant_profiles.profile.intent_gate: "on"): mutating tools gain a deterministic Tier-0 pre-flight (two-phase preview/confirm for supersession + delete, dependency-freshness flags, compact gate ack block), intent_open adds the Tier-1 memory-similarity critic, and Tier 2 (LLM reasoning over the direct Anthropic API — never MCP sampling) ships behind tier2: "on" (default off). Default-profile namespaces are byte-identical to the pre-gate server.

/healthz (liveness) and the /admin token dashboard are served separately (not MCP tools).

Tenancy — namespace is the project boundary

`namespace` == project == tenant. One namespace per project (e.g. acme-billing), with conventional sub-scopes by key prefix (coord/…, knowledge/…). Every per-project tool takes a required namespace and every query filters on it — there are no implicit cross-project reads. The session and session_event tables carry namespace too, so episodic memory is scoped like everything else.

Artifacts are the deliberate exception: they are content-addressed (sha256) and dedup globally, so they are not tenant-scoped — the hash is the capability.

Honest limit (and the v2 fix)

The per-surface tokens scope which client surface connects, not which project it may touch: any holder of any active token can pass any namespace, so namespace remains a soft boundary — real isolation for honest clients, not enforced against a misbehaving one.

v2 auth roadmap — per-project tokens/roles. A token scoped to

acme-billing must not be able to read or write other-project. Until then,

treat the namespace boundary as a convention enforced by client configuration,

not by the server. (See REUSABILITY.md → "namespace is the tenant boundary".)

Auth & the /admin dashboard

MCP tokens are stored in Postgres (admin_auth_tokens) and rotatable from `/admin` without a redeploy. There is one active token per surface:

surfacelabelhow the client sends it
claude.ai web connectorweb?token= in the URL (the web connector can't send headers)
Claude Desktop and the Claude Code CLIdesktop-cliAuthorization: Bearer
CursorcursorAuthorization: Bearer (via .cursor/mcp.json)

The gate accepts any active token, so each surface can be rotated or revoked independently — rotating web never disturbs desktop-cli or cursor. The /admin page shows one card per surface with a ready-to-paste URL/command and its own rotate button.

MCP_AUTH_TOKEN seeds the `web` token on initial boot (so an existing claude.ai connector keeps working); desktop-cli and cursor are auto-generated. After first boot the dashboard is the source of truth.

  • /admin is password-gated by `ADMIN_PASSWORD` (signed, HttpOnly session cookie, CSRF-protected). Without it the dashboard refuses logins.
  • The only routes not behind the bearer gate are GET /healthz, the streamed GET /artifact/{sha256}, and /admin (which self-authenticates).

Stateless transport. /mcp runs in stateless HTTP mode (http_app(stateless_http=True)): every request is self-contained, with no in-memory session affinity. Client sessions therefore survive VM restarts/redeploys, and the three surfaces share no server-side session state.

Architecture

  • One AsyncConnectionPool created in the FastAPI lifespan (app.py), injected via deps. Nothing else opens a connection. The pool is built with check=AsyncConnectionPool.check_connection, so a connection terminated server-side while idle is validated and discarded on checkout, never handed to a caller.
  • One config.py (pydantic-settings) — the only place secrets are read.
  • StorageBackend ABC (storage/base.py) implemented by PostgresBackend; the 18 tools map 1:1 onto it.
  • Transparent reconnect: reads and idempotent writes retry on a connection drop (_retry_on_disconnect), so e.g. OperationalError: terminating connection due to administrator command (SQLSTATE 57P01, Neon scale-down / PgBouncer) is retried on a fresh pooled connection instead of surfacing to the caller. Only genuine disconnects (08xxx / 57P0x / an already-closed connection) are retried — other operational errors (lock timeout, too-many-connections) surface unchanged. Writes retry only when a replay is safe: artifact_put (content-addressed) always, and memory_save/handoff_save/memory_delete only when given an event_id (exactly-once). The session_* writes also retry, with an explicit tradeoff: a drop in the narrow commit-ack window means session_create may orphan an empty, unreferenced session row, and session_append_event is at-least-once (a replay can append one duplicate event). For an append-only session log that beats failing the call outright; a save with no event_id still runs once and surfaces the error.
  • Write-path sanitize strips forged delimiters/control chars; reads wrap values in << >> markers (lethal-trifecta defense). Note: the value (and session-event payload) fields come back wrapped, so a consumer that needs the raw value — e.g. to json.loads a value that was a JSON string — must strip the markers first. Use storage.sanitize.unwrap_value (or strip_untrusted for a single string); the wrapping stays applied on every read.
  • Bounded lifespan readiness (no unbounded pool.wait()), 50 MB artifact cap, ranged blob reads, idempotent event_id writes, idempotent blob backfill.
  • Semantic recall (`memory_search`): when a VOYAGE_API_KEY is set, every memory_save embeds the entry (Voyage, voyage-3.5-lite, 1024-dim) into a nullable embedding vector(1024) column with an HNSW cosine index, and memory_search ranks live entries by meaning (embedding <=> query), then backfills keyword/substring matches up to limit. Embedding is best-effort: it runs before a connection is taken and never blocks (or fails) a write, and with no key the column stays NULL and search degrades to pure keyword — the pre-Phase-3 behavior. Every leg filters on namespace first (no cross-project recall). After enabling a key on an existing DB, embed old rows once with python scripts/backfill_embeddings.py (idempotent, only touches NULL rows).
  • Recall tuning (`hnsw.ef_search`): the HNSW index is approximate, so a larger store can miss relevant hits unless its query-time recall parameter is tuned. memory_search sets hnsw.ef_search per-statement (transaction-local, semantic leg only) from HNSW_EF_SEARCH (default 100; pgvector's own default is 40). Higher = better recall, slightly slower search; it must be >= the search limit to take effect. Small stores return the same rows regardless, so the default is safe to leave alone — raise it (e.g. 200) if a large tenant reports missing results, lower it toward 40 to shave latency. Very large tenants can also tune the index build parameters (m, ef_construction); see migrations/0002_embeddings.sql (changing those requires recreating the index).
  • Coordination reconciler (`coord_reconcile`): when GitHub access is available, a claim (with meta.repo + meta.pr/meta.branch) is resolved against live GitHub — is PR #N merged? what is branch X's head? — and stamped with an append-only verdict; without access it stays unverifiable (never a wrong current). Access is sourced in priority order: an explicit GITHUB_TOKEN (read-only repo + PRs), e

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