Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Offline code search for agents: find code by identifier, error message or plain description
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": {
"ripsem": {
"command": "npx",
"args": [
"-y",
"ripsem",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add ripsem -- npx -y ripsem mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"ripsem": {
"command": "npx",
"args": [
"-y",
"ripsem",
"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": {
"ripsem": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"ripsem",
"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 7일 점검
레지스트리 이름이 GitHub 계정 Sadykhzadeh 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(0.2.0)은 5일 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
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
ripsem
Where is the code that does this?
Get started · Usage · Coding agents · How it works · Troubleshooting
ripsem is local, offline code search for people and for coding agents. Ask with an identifier, an error message or a plain description of the behaviour, and get back the functions and types that answer it, ranked, with their names and line ranges.
ripsem install claude-code or ripsem install cursor adds an MCP server that keeps its index current while the agent edits, and tells the agent when to use it.npm (any platform): bash npm install -g ripsem
Cargo: bash cargo install --locked ripsem
macOS and Linux, without npm or Rust: bash curl -fsSL https://raw.githubusercontent.com/Sadykhzadeh/ripsem/master/install.sh | sh
Windows, without npm or Rust: powershell irm https://raw.githubusercontent.com/Sadykhzadeh/ripsem/master/install.ps1 | iex
bash ripsem search "strip the auth header when redirecting to another host"
ripsem install claude-code or ripsem install cursor (see below).The first search in a git repository, or in a directory where ripsem init has run, builds the index: it downloads the model (~133 MB) once and embeds the repository. Every search after that first embeds whatever changed since, so results never point at code that has moved. On Windows the first index runs on the GPU through DirectML when there is one.
grep answers "where does this string occur". That is the right question when you know the string. ripsem is for when you know what the code does but not what it is called: a description finds the function, and an identifier or an error message still finds its exact match, because the lexical arm sees it literally. Each hit is a whole function or type with its name, not a matching line, so a reader or an agent can tell a definition from a call site without opening the file.
npm and the install scripts put the prebuilt binary from the latest release on your PATH, after checking it against the release's SHA256SUMS. The scripts install to ~/.local/bin and %LOCALAPPDATA%\Programs\ripsem; RIPSEM_INSTALL_DIR overrides that. The release archives can also be unpacked by hand; on Windows, keep DirectML.dll next to ripsem.exe.
| platform | runs on |
|---|---|
x86_64-unknown-linux-gnu | glibc 2.35, libstdc++ 12 and OpenSSL 3 or newer: Ubuntu 22.04, Debian 12 and later |
aarch64-unknown-linux-gnu | glibc 2.39, libstdc++ 14 and OpenSSL 3 or newer on 64-bit Arm: Ubuntu 24.04, Debian 13 and later, such as on AWS Graviton; from the install script or the archive, not npm yet |
aarch64-apple-darwin | macOS 13.4 or newer on Apple silicon |
x86_64-pc-windows-msvc | Windows 10 or newer with the Microsoft Visual C++ Redistributable |
The embedding runtime in the x86-64 builds needs a CPU with AVX2 (Intel Haswell, AMD Excavator or newer). The binaries are built with the embedding runtime and tree-sitter; the model itself downloads on first use.
cargo install builds from source, with Rust 1.92 or newer. The build downloads a prebuilt ONNX Runtime, and needs a C and C++ compiler, plus pkg-config and the OpenSSL headers on Linux (build-essential pkg-config libssl-dev on Debian and Ubuntu).
Tagged releases are the stable versions, and npm, Cargo and the install scripts all install the latest one. master carries the changes for the next release, listed under Unreleased in CHANGELOG.md.
To build the latest release from a checkout:
git clone https://github.com/Sadykhzadeh/ripsem
cd ripsem git checkout "$(git describe --tags --abbrev=0)" cargo install --locked --path .
Leaving out the git checkout builds master.
The fastembed feature, on by default, pulls in the local embedding runtime. Built with --no-default-features, ripsem runs on a lightweight hashing backend that matches words instead of meaning, which is what the test suite uses.
The treesitter feature, also on by default, chunks code on function and type boundaries instead of fixed line windows, and names each chunk after the declaration it belongs to. Results look like src/auth/session.rs:40-72 fn Session::refresh, so a caller can tell a definition from a call site without opening the file. A function too large for one chunk passes its name to every piece. It covers Rust, Python, JavaScript, TypeScript, Go, Java, C, C++, C#, Ruby, PHP, Scala, Kotlin, Bash, HTML, CSS and JSON; other files are cut into line windows.
The hnsw feature adds an approximate-nearest-neighbour graph for indexes above 500 000 chunks. It changes only how the vector arm gathers candidates; the lexical arm and the merge work the same at any size.
ripsem completions bash > ~/.local/share/bash-completion/completions/ripsem
ripsem completions zsh > ~/.zfunc/_ripsem ripsem completions fish > ~/.config/fish/completions/ripsem.fish ripsem completions powershell >> $PROFILE
ripsem init # write .ripsem/config.toml
ripsem index # build the index (incremental on re-runs) ripsem search "where is auth set up?" # updates the index first ripsem status # index size, counts, model, drift from the tree ripsem status --json # the same as JSON (schema ripsem/status/v1) ripsem watch # keep the index in sync as files change
Like git, every command except init works from any subdirectory: it uses the nearest parent that holds a .ripsem directory. --path overrides that.
The index stays out of git: .ripsem/.gitignore lists it, so git status shows only config.toml (which can be committed) and that .gitignore. ripsem writes the file when it is missing and never changes an existing one.
status also reports how far the index has drifted from the files. Hits carry the line range their file had when it was indexed, so tree: out of date: 3 changed, 1 new tells you when a result may no longer point at the right lines. Drift is measured with the same content hash the incremental index uses, so it counts exactly what a rebuild would touch. The JSON carries it as index.drift (added/modified/removed).
Results print as path:start-end with the declaration's name and a snippet, in merged-ranking order. The first three hits carry their code, up to 40 lines, so the answer can be read without opening the file. Records that cover the same lines (a declaration and the documentation above it, or adjacent windows) are returned once, so -k 5 means five distinct places. The number shown runs from 0 to 1: how far the hit's meaning rises above unrelated text in this repository, or the share of the query's terms found literally, whichever is higher. It never rises down the list, so a threshold keeps the top of the ranking. Each index measures its own noise floor by matching queries about anything but code against it, so the scale follows the repository and the model.
The words of a query need no quotes: ripsem search where is auth set up asks the same as ripsem search "where is auth set up".
-k sets the number of results (default 10).--json prints the hits as a JSON array. Each has path, start_line, end_line, score, kind and symbol (such as fn and Session::refresh, both null for a hit outside any declaration) and snippet. With --count-by-file each entry is a path and its count.--in limits results to a subdirectory. A relative path starts from the current directory, as in the shell: in src, --in auth means src/auth and --in . means src. An absolute path into the repository works too.--context sets how many snippet lines print per hit (3 in a terminal, the whole snippet when the output goes to another program; 0 prints just the locations).--min-score keeps only strong matches, in both human and JSON output.--count-by-file prints hit counts per file instead of the hits.ripsem model list # show available models
ripsem model set bge-base-en-v1.5 ripsem index # rebuilds the index for the new model
| Model | Dims | Disk | Notes |
|---|---|---|---|
| bge-small-en-v1.5 | 384 | ~133 MB | default |
| all-MiniLM-L6-v2 | 384 | ~90 MB | smallest and fastest to embed |
| bge-base-en-v1.5 | 768 | ~436 MB | larger English model |
| multilingual-e5-small | 384 | ~470 MB | queries and comments in other languages |
| nomic-embed-text-v1.5 | 768 | ~550 MB | larger English model, the most memory to index |
The model downloads once on first use, then everything is offline.
ripsem install claude-code # .mcp.json and a note in CLAUDE.md
ripsem install cursor # .cursor/mcp.json and a rule in .cursor/rules
install registers the server, writes .ripsem/config.toml, and adds a short note that tells the agent to reach for search before grepping. Restart the agent in the directory and it can call search directly.
The server sends the same note as its MCP instructions. Claude Code loads the descriptions of MCP tools only when the model looks a tool up, so the model learns that search exists, and when to use it, from the instructions and the note in CLAUDE.md.
ripsem mcp speaks MCP over stdio and exposes a single search tool: a query, and optionally a path to stay inside, a limit (default 5, at most
min_score. An argument outside the schema comes back as a toolerror that names what is exp
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