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Local codebase memory and repository code search for Codex, Claude Code, and MCP coding agents.
About
Local codebase memory and repository code search for Codex, Claude Code, and MCP coding agents.
Security Report
Valid MCP server (3 strong, 4 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
8 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-vibhu-dixit-lybrary": {
"args": [
"lybrary"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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.
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