Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Context sync layer for AI agents. Ensures continuity and eliminates memory drift automatically.
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": {
"context-fabric": {
"command": "npx",
"args": [
"-y",
"context-fabric"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add context-fabric -- npx -y context-fabric프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"context-fabric": {
"command": "npx",
"args": [
"-y",
"context-fabric"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"context-fabric": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"context-fabric"
]
}
}
}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 7일 점검
레지스트리 이름이 GitHub 계정 VIKAS9793 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(1.2.2)은 4개월 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.
Current stable release: v1.2.2. See CHANGELOG.md for the release notes.
Context Fabric is configured for official inclusion in the Model Context Protocol (MCP) Registry.
io.github.VIKAS9793/context-fabricThe context synchronization layer for AI coding agents. Ensure project continuity, eliminate agent memory drift, and manage token budgets automatically across any coding session.
Context Fabric is an MCP server that automatically captures project state on every git commit, detects when stored context has drifted from codebase reality, and delivers structured, token-budgeted briefings to AI agents — without requiring any developer action.
Developers using AI coding agents manually construct and maintain documentation systems, session handoff rituals, and context workflows to compensate for the absence of native project continuity tooling. These workarounds share one property: they go stale after commits, and nothing detects it.
The problem is not that AI forgets. The problem is context drift — stored context becomes incorrect after code changes, and AI agents proceed with that incorrect context confidently.
Context Fabric is the infrastructure layer that solves it at the root.
Context Fabric is powered by CADRE, a five-engine internal architecture. Every engine solves a specific, documented failure mode observed in real developer workflows.
What CADRE is. CADRE is the automated replacement for every manual context management system developers currently build themselves. It sits between the git event stream and the AI agent, deciding what context to capture, when it has drifted, which parts are relevant to the active query, what they cost in tokens, and how to deliver them structured and reliably.
Who CADRE is for. Developers building multi-session AI-assisted software projects who currently spend time on any of the following: updating markdown files after commits, creating session-end summaries, maintaining CLAUDE.md or AGENTS.md files, building RAG pipelines for project context, or manually deciding which documentation to load before each task.
E1 — WATCHER
Installs a git post-commit hook on context-fabric init. Fires automatically on every commit. Reads committed Git blobs instead of the mutable working tree, computes SHA256 fingerprints, extracts exported symbols, calculates token estimates, and upserts everything into the local SQLite store. The developer does nothing after setup.
Replaces: markdown-per-commit workflows, 5-step session rituals, and AI interview workflows used to extract structured project knowledge before sessions.
E2 — ANCHOR
On every cf_query call, compares stored SHA256 hashes against the current state of every tracked file. Returns a DriftReport with a 0–100 drift score and severity classification: LOW (under 10%), MED (10–30%), HIGH (over 30%). Stale files are identified by path and hash delta.
Replaces: manual documentation alignment reviews and the undetected staleness in AGENTS.md that ETH Zurich research (arXiv:2602.11988) demonstrated degrades AI coding performance.
E3 — ROUTER
Runs SQLite FTS5 BM25 against the stored component index using the query text from cf_query. Returns components ranked by relevance. Path matches are weighted 2x over export symbol matches, because a file path carries structural meaning about the codebase organisation. Falls back to recency sort when the query produces zero MATCH results.
Replaces: manual selection of which documentation to include per task, and the modular context selection problem that emerges when projects decompose knowledge across many files.
E4 — GOVERNOR
Applies a configurable token budget ceiling to the E3 ranked output using greedy selection on the relevance-ordered list. Default: 8% of the model context window, leaving 92% for conversation and code. Oversize components are skipped so the remaining budget can still be used by later-ranked matches. Token estimates pre-calculated by E1 mean zero additional file reads at budget selection time.
Replaces: manual token management, and the pattern of keeping sessions alive indefinitely to avoid the cost of context restoration on restart.
E5 — WEAVER
Composes a structured markdown briefing from E3 and E4 output. Sections: Project State, Architecture, Architecture Decisions, Budget Summary. When E2 severity is MED or HIGH, a Drift Warning section is prepended before all other content, so the AI is informed of context reliability before reading it.
Replaces: static AGENTS.md briefings that never update, and the manual briefing preparation that developers perform at every session start.
git commit
| v E1 WATCHER --- SHA256 fingerprint --- SQLite upsert --- FTS5 index update | cf_query("...") | v E2 ANCHOR --- drift check --- DriftReport | v E3 ROUTER --- FTS5 BM25 --- ranked component list | v E4 GOVERNOR --- greedy selection --- budget-capped set | v E5 WEAVER --- briefing composition --- MCP response
npx context-fabric init
Initialises the SQLite store, installs the git post-commit hook, stages the stable local runtime under .context-fabric/runtime, and runs an initial capture. Connect the MCP server to your tool and context delivery is active from the next commit.
npx context-fabric init
Windows Users (Crucial):
{
"mcpServers": { "context-fabric": { "command": "cmd", "args": ["/c", "npx", "context-fabric"] } } }
Mac / Linux Users:
{
"mcpServers": { "context-fabric": { "command": "npx", "args": ["-y", "context-fabric"] } } }
Use the health commands when validating a local install or recovering from a broken hook/runtime state.
npx context-fabric doctor
npx context-fabric doctor --repair
doctor reports schema version, search index version, DB integrity, degraded mode, pending and failed captures, plus hook runtime readiness. doctor --repair refreshes the local runtime bundle, reinstalls the stable hook wrapper, validates .gitignore, and rebuilds the search index when the database is healthy.
spawn npx ENOENT ErrorsThis usually means npx is not in the system's inheritance path for the IDE.
node and the context-fabric binary.where node (Windows) or which node (Mac/Linux) to find your path. "command": "/Users/name/.nvm/versions/node/v22.14.0/bin/node",
"args": ["/Users/name/.nvm/versions/node/v22.14.0/bin/context-fabric"]
If you run VS Code on Windows but your code is in WSL, you must run init inside the WSL terminal and use the WSL-absolute path to node in your config.
On Windows, spaces in your project path (e.g., C:\My Projects\app) can break the npx spawn. If the server fails, consider moving your project to a path without spaces.
If something breaks, please run:
npx context-fabric doctor
npx context-fabric diag remains available as a compatibility alias.
Does Context Fabric send my code to a server? No. It is local-only and does not make outbound network calls for capture, retrieval, or drift analysis.
Does it index uncommitted changes? No. Captured state is based on committed Git objects. Uncommitted changes are detected by drift checks, but they are not indexed as the new source of truth until you commit and capture them.
Is this a replacement for `AGENTS.md`, `CLAUDE.md`, or human docs? It reduces the need for manual session-handoff documents, but it is not a replacement for product specs, onboarding guides, or stakeholder-facing documentation.
What files does it write locally? It writes under .context-fabric/ for the database and runtime bundle, and installs .git/hooks/post-commit to keep capture automatic.
When should I not use it? Do not use Context Fabric if you need cloud sync, cross-repo search, full semantic indexing of implementation bodies, or project-file mutation from MCP tools.
How do I recover a broken install? Run npx context-fabric doctor first. If the hook runtime or local state needs repair, run npx context-fabric doctor --repair.
Full FAQ: docs/FAQ.md
| Tool | Engines | Purpose |
|---|---|---|
cf_capture | E1 | Manual context capture outside of a git commit |
cf_drift | E2 | Standalone drift check — returns severity and stale file count |
cf_query | E2 + E3 + E4 + E5 | Full context briefing for the current task |
cf_health | Local health | Report database, capture, hook, and search index health |
cf_log_decision | Storage | Persist an architecture decision across sessions |
All tools expose MCP annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) as of 1.1.0. cf_capture, cf_drift, cf_health, and cf_log_decision also return structuredContent alongside their text output; cf_query intentionally does not, since its output is prose meant for injection into an agent's context window rather than a
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