Lybrary

Name: Lybrary
Author: vibhu-dixit

by vibhu-dixitversion 0.3.2i★ –iRuns on your computer

Registry nameio.github.vibhu-dixit/lybrary

Install

Overview

Description from the maker (original English)

Local codebase memory and repository code search for Codex, Claude Code, and MCP coding agents.

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
UsageiVery new↓ 35/wk · ★ –

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: Developer tools

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": {
    "lybrary": {
      "command": "uvx",
      "args": [
        "lybrary"
      ]
    }
  }
}

Run this in your terminal

claude mcp add lybrary -- uvx lybrary

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "lybrary": {
      "command": "uvx",
      "args": [
        "lybrary"
      ]
    }
  }
}

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": {
    "lybrary": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "lybrary"
      ]
    }
  }
}

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 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account vibhu-dixit, 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 Developer toolsi

More stars than 0% of the other 4927 servers in this category
Published to the registry more recently than 61% of the other 4927 servers in this category
Basic checks equal to or better than 100% of the other 4927 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 Lybrary 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 (0.3.2) reached the registry 26 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: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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

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

GitHub

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

by githubWidely used★ 34.2KUpdated 5 days ago

Computer or cloud

Install

Desktop Commander

MCP server for terminal commands, file operations, and process management

by wonderwhy-erWidely used↓ 709.6K/wk★ 10.2KUpdated 17 days ago

Runs on your computer

Install

Cloudflare MCP

Cloudflare MCP servers

by cloudflareGrowing★ 4.4KUpdated 14 months ago

Runs in the cloud✓ mcp.cloudflare.com

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.

Lybrary — local codebase memory for coding agents

Lybrary indexes a repository by code structure and gives Codex, Claude Code, and other MCP clients a searchable map of its functions, classes, and files. It runs locally, watches for changes, and lets an agent find relevant source lines before opening whole files.

PyPI · Documentation · Agent setup guide · Source · Issues

If you want a coding agent to set this up, ask it to find and install a local MCP code search tool for the repository and point it to the agent setup guide. The guide identifies the PyPI package, source repository, install command, and checks that confirm the agent is using this repo's index.

Start in any repository

Install once, then run lybrary start in each folder you want indexed:

pip install lybrary

cd /path/to/your/repo lybrary start lybrary status

start creates .lybrary/ if needed, builds the index, and runs a file-watching daemon in the background. It keeps running after the terminal closes. Run lybrary stop in that repository to stop it. The first indexing run may download the local embedding model; later runs use the cache.

Each repository has its own index and .lybrary/config.toml. The index stays on your machine; no API key or hosted database is required.

Connect an agent

Register the MCP server once on your machine. Start your agent in an indexed repository, then ask it to call memory_status to confirm the root and chunk count.

Codex

Codex users can install Lybrary's setup skill from the repository's plugin marketplace:

codex plugin marketplace add vibhu-dixit/lybrary

codex plugin add lybrary@lybrary

The plugin helps with setup; register the local MCP server separately:

codex mcp add lybrary -- lybrary mcp

codex mcp list

Add this to that repository's AGENTS.md if you want Codex to use the memory consistently:

When .lybrary/index.db exists, use Lybrary memory_query before broad code searches or reading multiple files. Inspect the returned source paths and lines before editing. If the index is absent or the tool fails, use normal search.

Claude Code

Claude Code users can install the repository's plugin, which registers the MCP server and includes a setup skill:

claude plugin marketplace add vibhu-dixit/lybrary

claude plugin install lybrary@lybrary

The Python package must also be installed with pip install lybrary. Or register the MCP server directly without the plugin:

claude mcp add --scope user --transport stdio lybrary -- lybrary mcp

claude mcp list

In Claude Code, /mcp shows connection status. Put the same instruction in the repository's CLAUDE.md. Registration makes the tool available; the instruction helps the agent choose it when useful.

For another stdio MCP client, configure command lybrary with argument mcp. See the setup guides.

What the agent gets

memory_query checks exact symbols and an SQLite FTS5 index first. Strong lexical matches avoid loading the embedding model; semantic search remains a fallback when wording does not match the code. Its default response gives ranked paths, symbols, line ranges, and compact numbered excerpts. If a trace crosses a named call missing from the first result, query that symbol once. Set include_content=true when a full chunk is needed.

memory_status reports the active repository and index health. memory_update triggers incremental, full, or path-scoped re-indexing.

This can avoid repeated broad searches and large file reads, especially when the agent needs to locate a feature across sessions. Actual token use depends on the task, the agent's tool choices, and how much source it still needs to inspect. The benchmark guide explains how to compare complete runs rather than infer savings from the size of one response.

Make it fit your repo

Edit .lybrary/config.toml to choose the embedding model and device, chunk sizes, indexed languages, excluded paths, and file-watcher debounce. Add Git-style ignore patterns to .lybrary/ignore. Re-run lybrary index --full after changing settings that affect stored chunks or embeddings.

Supported parsers: Python, JavaScript, TypeScript, TSX, Go, Rust, Java, C, and C++. The indexer uses tree-sitter boundaries and refreshes changed files while the daemon is running.

CLI

Command	Purpose
`lybrary start`	Initialize, index, and watch the current repository
`lybrary stop`	Stop its background daemon
`lybrary status`	Show daemon and index status
`lybrary query "authentication flow"`	Search from the terminal
`lybrary index --full`	Rebuild the index
`lybrary logs`	Show daemon logs
`lybrary mcp`	Run the stdio MCP server

If an agent starts above the indexed repository, pass that repository's absolute path as repo_root to the MCP tool, or start the agent inside it.

Measure the effect

From a source checkout, compare the same read-only question with and without Lybrary:

python benchmark.py /path/to/indexed/repo "Trace how interview invitations are sent"

The script records both answers, tool calls, and total, cached, and uncached input tokens under .lybrary/benchmarks/. Check answer correctness first; one question does not establish typical savings.

Contribute

Issues and pull requests are welcome. For a local checkout:

pip install -e ".[dev]"

pytest

Lybrary is MIT licensed. See the changelog for releases.

Lybrary

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 Developer toolsi

Common questions

Alternatives

GitHub

Desktop Commander

Cloudflare MCP

README from the maker

Lybrary — local codebase memory for coding agents

Start in any repository

Connect an agent

Codex

Claude Code

What the agent gets

Make it fit your repo

CLI

Measure the effect

Contribute