Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Local-first automatic memory for Claude Code and Codex: capture, distill, recall from SQLite.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"remem": {
"command": "npx",
"args": [
"-y",
"@remem-ai/remem",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add remem -- npx -y @remem-ai/remem mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"remem": {
"command": "npx",
"args": [
"-y",
"@remem-ai/remem",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"remem": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@remem-ai/remem",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 majiayu000 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
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.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.6.104)은 31일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Stop re-explaining your project every new coding-agent session.
Language: English | 简体中文
remem automatically captures, distills, searches, and injects engineering memory across Claude Code and OpenAI Codex CLI sessions. Decisions, bug-fix rationale, project patterns, and preferences stay available through hooks, MCP, CLI, and a localhost REST API.
*A new Claude Code session recalls the earlier root cause, commit, and open TODO with memory citations and no re-explaining.*
The optional DSH adapter injects project context and captures live prompts, assistant text, and tools using the existing CLI. It targets published DSH 0.2.0-rc.2; the npm adapter is not yet published. Build the DSH-enabled remem 0.7.0 source before installing the adapter. Assistant-only claims remain available for review and cannot auto-promote without independent supporting evidence. Snapshot updates and removals respect the published DSH session invariant; remem preparation failures retain uncommitted prompts for an explicit retry, while cancellation leaves durable capture available to flush. Recovery across unload lasts until the in-flight remem callback exits; while loaded, agent/error also recovers later preparation failures. Host prepareCall runs after agent/request returns: after unload, failure can lose claimed input, while success still commits once without remem capture. Reload does not recover lost input or import events committed while unloaded. Oversized prompts, assistant messages, turn summaries and tool observations retain bounded evidence with explicit omissions before core redaction. Arbitrary DSH tool names retain their provenance but are external evidence; their names alone never authorize automatic promotion.
remem prioritizes memory quality. Automatic capture is the primary path; manual save_memory calls supplement it when a decision needs to be recorded immediately.
brew install majiayu000/tap/remem
"$(brew --prefix remem)/bin/remem" install --target codex
Use --target claude for Claude Code. --target all configures every known host, including Cursor where its v1 renderer is supported.
curl -fsSL https://raw.githubusercontent.com/majiayu000/remem/main/install.sh | env REMEM_NO_CONFIG=1 sh
~/.local/bin/remem install --target codex
npm install -g @remem-ai/remem
cargo install remem-ai --bin remem
remem install --target codex
Codex installation, detection, doctor, uninstall, transcript scanning and default native-memory import all honor CODEX_HOME; the default is ~/.codex. Set it to an absolute directory before running these commands to select another Codex profile. Empty or relative overrides fail visibly before installation writes. Unrelated profile files stay untouched.
GitHub Releases: prebuilt binaries for macOS and Linux on x64/arm64, with published checksums. Use one canonical remem executable on PATH; remem doctor warns when hooks and terminals resolve different copies.
For channel-specific upgrades, platform boundaries, PATH drift, and manual install notes, read the installation and upgrade guide. The broader documentation guide links plugin and operational material.
Restart the selected coding agent, then run:
remem doctor
remem status remem search "last decision"
A healthy Claude Code or Codex installation injects relevant project memory at SessionStart and queues durable session distillation at Stop. Codex also uses UserPromptSubmit to capture each prompt and surface compact optional memory candidates. remem doctor checks the schema, encryption key, database, hooks, MCP registration, worker, and common install-path drift. Its diagnostics do not create the data directory or write or rotate log files; findings and stderr warnings remain visible, and existing log health is inspected.
Repository contributors can verify duplicate SessionStart suppression with the isolated executable smoke fixture.
For a focused, read-only view of current-memory truth:
remem doctor truth --cwd .
Use one read-only report to follow capture, extraction, review, current validity, and the latest recorded context run:
remem doctor memory "original phrase" --cwd .
remem doctor memory --host codex-cli --source-root local \ --project PROJECT_KEY --session-id SESSION_ID --json
Copy the exact selector from remem raw sessions --json. Use --injection-run-id RUN_ID to inspect a specific destination context emission. The source session and destination context run are distinct. Each evidence source is bounded at 20 rows; omitted evidence is marked. Terminal output shows retained source/status counts and three samples per source; --json includes all retained evidence. A missing match or per-item audit is unknown, not proof that capture failed or a guessed drop reason. Query discovery combines raw search with literal stored-text matches; try an original phrase or the exact session when a paraphrase finds no evidence. See the diagnosis contract.
Remem helps an Agent continue work; Refine helps people inspect and reuse knowledge; agent-sessions parses native source formats. Refine consumes Remem's existing session references, content fingerprints and commit/session links instead of collecting another transcript copy.
| Capability | Claude Code | Codex CLI | Cursor v1 |
|---|---|---|---|
| MCP memory tools | Yes | Yes | Yes on macOS/Linux |
| SessionStart injection | Yes | Yes | Not supported |
| Automatic session memory | Yes | Yes, Stop-based and low-noise | Not enabled by the v1 installer |
| Tool-event capture | Installed hooks | No high-frequency Bash hook by default | Runtime command exists; no installed hook |
| Compiled command-rule enforcement | Optional warn/block on Bash | Not supported | Not supported |
| Windows | Supported | Supported | Not supported |
Cursor's v1 installer registers MCP only. The verified observe and summarize runtime commands exist, but remem install --target cursor does not install automatic capture hooks or SessionStart injection.
The repository also includes a Codex plugin wrapper. See plugins/remem/README.md for local plugin runtime and explicit hook activation instructions.
Built-in MEMORY.md, CLAUDE.md, and agent instruction files are ideal for a small set of stable facts that should always be visible. remem covers the engineering history that is too large, dynamic, or evidence-heavy to maintain by hand.
| Need | Built-in files | remem |
|---|---|---|
| Stable project rules | Excellent | Supported |
| Evolving context | Handwritten instructions; Claude Code auto memory also writes notes | Hook-driven session capture and background distillation |
| Search older rationale | Limited by loaded text | Curated and raw search |
| Branch, time, and staleness handling | Manual | Built in |
| Provenance and injection audit | Git history | Database-backed audit |
| Review, suppression, and lifecycle governance | Manual edits | First-class commands |
Claude Code auto memory already saves notes automatically. The distinction is the memory surface and its evidence, retrieval, and lifecycle controls, rather than automatic persistence alone.
Use both. Keep concise rules in native files and let remem retain the long tail of decisions, failures, evidence, and changing project state.
The broader ecosystem comparison lives in the dated memory-tool survey.
Claude Code / Codex hooks
| v append-only captured_events ledger | v coalesced background extraction and session rollup | v governed candidates -> curated memories + workstreams + raw archive | v FTS, entity, temporal, vector, graph, and optional local rerank retrieval | v budgeted, source-attributed SessionStart context
Hooks return quickly after durable capture or queueing. Background workers perform extraction, candidate governance, compression, retrieval enrichment, and lifecycle cleanup. MCP, CLI, REST, and SessionStart share the same local store and governance model, but apply surface-specific eligibility policies. Explicit search is an inspection and recovery surface, so it may return labeled legacy_unverified memories; default SessionStart and CurrentTruth exclude those rows and record the reason.
Malformed generated extraction responses retry with the existing bounded backoff while keeping the same source evidence. Invalid stored evidence still requires repair; exhausted model attempts preserve raw capture and replay ranges for inspection instead of accepting incomplete output.
Observation extraction and session rollup split large backlogs into bounded event chunks. Each model call budgets system instructions, prompt formatting, and evidence together; completion advances only through the processed chunk. Raw evidence remains available when per-event prompt content is clipped. Exact recovery retains the original range and resumes verified successful chunks under the explicitly selected profile and one overall timeout. Already-existing linked successors resume from their own original bounds and checkpoints; a completed primary task does not hide a failed successor. Archived exact recovery claims the existing family atomically, suppresses new follow-up work, and archives unfinished members again if the attempt fails.
Workers persist fair queue and stage/project claim order, so continuing capture in a busy project leaves room for downstream extraction and durable jobs across once-worker restarts. The existing once-worker admission budget still applies.
Generated memory is treated as untrusted until it passes source-support, secret, instruction-pattern, scope, and lifecycle checks. Unsafe content is dropped or routed to review with a diagnosable reason. Complete, user-supported security prohibitions, research activities and explicitly analytical quotations can enter human review in English or Chinese; they never auto-promote. Secret values, harmful instructions and unsupported external te
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요