Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

ripsem

by Sadykhzadehversion 0.2.0i★ –iRuns on your computer
Registry nameio.github.Sadykhzadeh/ripsem

Install

Overview

Description from the maker (original English)

Offline code search for agents: find code by identifier, error message or plain description

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "ripsem": {
      "command": "npx",
      "args": [
        "-y",
        "ripsem",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add ripsem -- npx -y ripsem mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ripsem": {
      "command": "npx",
      "args": [
        "-y",
        "ripsem",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ripsem": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "ripsem",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Sadykhzadeh, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7259 servers in this category
  • Published to the registry more recently than 86% of the other 7259 servers in this category
  • Basic checks equal to or better than 100% of the other 7259 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is ripsem safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.0) reached the registry 5 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today
Install

Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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.

  • Every shape of question in one query. BM25 over code-aware tokens and vector similarity from a local embedding model, merged into one ranking. A chunk holding every term of an identifier or an error message comes first.
  • Answers are declarations. A hit is a whole function or type, named after it, in 17 languages, so a definition reads apart from a call site. A search for a name lands on its declaration, with its own lines and label.
  • Made for coding agents. 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.
  • Offline. No account, no API key, no service. The model downloads once and runs on your CPU, and the index is one file inside your repository.

Get started

  1. Install ripsem:

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

  1. In your repository, ask it something:

bash ripsem search "strip the auth header when redirecting to another host"

  1. Hand the same search to your coding agent with 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.

Why not grep?

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.

Install

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.

platformruns on
x86_64-unknown-linux-gnuglibc 2.35, libstdc++ 12 and OpenSSL 3 or newer: Ubuntu 22.04, Debian 12 and later
aarch64-unknown-linux-gnuglibc 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-darwinmacOS 13.4 or newer on Apple silicon
x86_64-pc-windows-msvcWindows 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.

Shell completions
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

Usage

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.

Models

ripsem model list                 # show available models

ripsem model set bge-base-en-v1.5 ripsem index # rebuilds the index for the new model

ModelDimsDiskNotes
bge-small-en-v1.5384~133 MBdefault
all-MiniLM-L6-v2384~90 MBsmallest and fastest to embed
bge-base-en-v1.5768~436 MBlarger English model
multilingual-e5-small384~470 MBqueries and comments in other languages
nomic-embed-text-v1.5768~550 MBlarger English model, the most memory to index

The model downloads once on first use, then everything is offline.

Use with coding agents

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

  1. and a min_score. An argument outside the schema comes back as a tool

error that names what is exp

Only the beginning is shown; read the rest in the repo

Ask PopNx