lanternkb

Name: lanternkb
Author: ankitb073

by ankitb073version 0.1.3i★ –iRuns on your computer

Registry nameio.github.ankitb073/lanternkb

Install

Overview

Description from the maker (original English)

Private, local search over your own files, by meaning and keywords, with secrets redacted.

PopNx MCP’s three pillars

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

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

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

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "lanternkb": {
      "command": "uvx",
      "args": [
        "lanternkb",
        "serve",
        "--tier",
        "open"
      ]
    }
  }
}

Run this in your terminal

claude mcp add lanternkb -- uvx lanternkb serve --tier open

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "lanternkb": {
      "command": "uvx",
      "args": [
        "lanternkb",
        "serve",
        "--tier",
        "open"
      ]
    }
  }
}

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": {
    "lanternkb": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "lanternkb",
        "serve",
        "--tier",
        "open"
      ]
    }
  }
}

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 ankitb073, 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 7249 servers in this category
Published to the registry more recently than 60% of the other 7249 servers in this category
Basic checks equal to or better than 100% of the other 7249 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 lanternkb 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 (0.1.3) reached the registry 25 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) 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.

lanternkb

Private, local search over your own files, for you and the AI tools you choose.

lanternkb indexes the folders you pick and searches them by meaning and by exact words. It runs as a local MCP server for Claude Code and other assistants, with no daemon, no open port and no telemetry. Secrets it detects are redacted before anything is stored, and you decide which folders an assistant that sends results to the cloud may see.

Install

macOS 14 or later on Apple silicon, or Linux, with uv:

uv tool install --managed-python --python 3.12 "lanternkb[embed,ui]"

lanternkb setup # asks for folders and whether an assistant may see them, offers the models, indexes

--python 3.12 matters: without it uv may pick an older Python already on the machine, and the install fails. The install takes about 0.9 GB on macOS, plus about 1.2 GB for the embedding model. uv tool upgrade lanternkb updates it.

Search

lanternkb search "what did the plumber say about the boiler"

lanternkb search "boiler quote" --type pdf,docx --since 30d lanternkb recent # files changed lately lanternkb ui # the settings page, with a search box lanternkb doctor # checks the setup and says what to fix

Run lanternkb setup before connecting an assistant: the server searches the folders you chose there.

Use it from your AI tools

Claude Code:

lanternkb mcp-setup prints a claude mcp add command. Run it.
The server it registers returns files from folders you marked open, and nothing else.
Claude Code can also read files with its own tools, so mcp-setup prints deny rules too. Add them to ~/.claude/settings.json to keep its tools away from your local-only folders and the index.

Codex, Cursor, VS Code, Gemini CLI and any other MCP client: run lanternkb serve --tier open as a stdio server. For Codex, in ~/.codex/config.toml:

[mcp_servers.lanternkb]

command = "lanternkb" args = ["serve", "--tier", "open"]

The user guide has the JSON form the other clients take, and what to watch for.

What it reads

Notes, code, PDFs, Word and OpenDocument files, rich text, saved web pages and subtitles; scanned pages and audio optionally. Plugins can add file types, embedding models and rules for which folder is open (plugins).

Privacy and safety

Every folder is open or local-only, and new folders are local-only.
Credential folders and secret-shaped files are skipped, and a secret scanner redacts what it finds before anything is split up or embedded. A file in which it finds a secret becomes local-only, even in an open folder.
Files are read in sandboxed worker processes that deny by default: sandbox-exec on macOS, Landlock and seccomp on Linux.
Nothing goes over the network except the model downloads you agree to.

The threat model says what is protected and what is not.

How well it works

Tested on a synthetic set of files (three open-source code bases and 654 generated notes) with 330 held-out questions: nDCG@10 0.831, against 0.777 for grooveseek with its reranker and 0.760 for QMD, at about 30 ms a search (about 120 ms with reranking, on an M5 Max). On the hardest held-out test of planted fake secrets, the scanner kept 71.9% out of the index, so treat it as a second line of defence: keep credential folders out of indexed folders, or local-only.

Limits

The secret scanner misses some secrets, and values that read as examples (example, changeme, a , a ${VARIABLE}) are left alone.
On Linux, reranking runs on the CPU at 0.4 to 1 s a search, so it is off until you enable it.
Email, browser history, calendars and contact cards are not indexed.
Scanned PDFs and images need OCR, which is off by default.

User guide
Plugins
Threat model
Security policy

Licence

Apache-2.0: see LICENSE, NOTICE and THIRD_PARTY_NOTICES.md.

lanternkb

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

lanternkb

Install

Search

Use it from your AI tools

What it reads

Privacy and safety

How well it works

Limits

More

Licence