# Turbo Quant Memory A local store of decisions and notes for your coding agent. Search hands back short cards instead of whole documents, and nothing leaves your machine. - MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI · ★ 9 - Author: Lexus2016 - License: MIT · policy=link-only · description only; the file stays with the author - Source: https://github.com/Lexus2016/turbo_quant_memory - Updated: 2026-10-24 - HTML: https://affpapa.org/en/nevibecode/mcp/turbo-quant-memory ## What it does The server gives an agent a persistent place to write while it works: decisions, lessons, patterns, session handoffs. It also keeps a compact index of your Markdown. A search returns cards of roughly 220 characters, and the agent pulls full content only when a card falls short. That is how it stops re-reading the same files and re-deriving the same conclusions. Retrieval is hybrid: BM25 combined with dense vector search through RRF. There is a knowledge graph with lifecycle and linting. Cyrillic matches exactly out of the box, no extra setup. The package exposes 24 MCP tools, and `server_info()` reports the token savings it has accumulated, so you can check the numbers rather than take them on faith. Python 3.11 or newer is required. On the first run `fastembed` pulls an embedding model of about 0.22 GB from Hugging Face, so that step needs a network connection; after it the server runs offline. There is no HTTP client and no telemetry in the package. Coming from 0.27.x or earlier, note that the distribution was renamed in 0.28.0, so `uv tool upgrade turbo-memory-mcp` no longer resolves — run `uv tool install --force turbo-quant-memory` once. ## Requirements - Needs: Python and uv (commands run via uvx) - Environment variables: `TQMEMORY_FTS_LANGUAGE`, `TQMEMORY_EMBEDDING_BACKEND`, `TQMEMORY_MIGRATE_ON_STARTUP`, `TQMEMORY_SECRETS_PASSPHRASE` — keys and tokens: ask the human for the values, never commit them or put them in shared files. ## Install ### Claude Code (native platform) **Platform CLI** ```bash claude mcp add --env TQMEMORY_FTS_LANGUAGE= --env TQMEMORY_EMBEDDING_BACKEND= --env TQMEMORY_MIGRATE_ON_STARTUP= --env TQMEMORY_SECRETS_PASSPHRASE= --transport stdio turbo-quant-memory -- uvx turbo-quant-memory ``` Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from turbo-quant-memory ### Codex **Platform CLI** ```bash codex mcp add turbo-quant-memory --env TQMEMORY_FTS_LANGUAGE= --env TQMEMORY_EMBEDDING_BACKEND= --env TQMEMORY_MIGRATE_ON_STARTUP= --env TQMEMORY_SECRETS_PASSPHRASE= -- uvx turbo-quant-memory ``` Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from turbo-quant-memory ### Cursor **Config file** File `.cursor/mcp.json`: ```json { "mcpServers": { "turbo-quant-memory": { "command": "uvx", "args": [ "turbo-quant-memory" ], "env": { "TQMEMORY_FTS_LANGUAGE": "", "TQMEMORY_EMBEDDING_BACKEND": "", "TQMEMORY_MIGRATE_ON_STARTUP": "", "TQMEMORY_SECRETS_PASSPHRASE": "" } } } } ``` Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from turbo-quant-memory ### GitHub Copilot **Config file** File `.vscode/mcp.json`: ```json { "servers": { "turbo-quant-memory": { "type": "stdio", "command": "uvx", "args": [ "turbo-quant-memory" ], "env": { "TQMEMORY_FTS_LANGUAGE": "", "TQMEMORY_EMBEDDING_BACKEND": "", "TQMEMORY_MIGRATE_ON_STARTUP": "", "TQMEMORY_SECRETS_PASSPHRASE": "" } } } } ``` Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from turbo-quant-memory ### Gemini CLI **Platform CLI** ```bash gemini mcp add -e TQMEMORY_FTS_LANGUAGE= -e TQMEMORY_EMBEDDING_BACKEND= -e TQMEMORY_MIGRATE_ON_STARTUP= -e TQMEMORY_SECRETS_PASSPHRASE= turbo-quant-memory uvx turbo-quant-memory ``` Replace <…> with your own values. uvx runs the command named after the package; if the README names another one, use uvx --from turbo-quant-memory ## When to use it - keep session decisions after the context compacts - find what the team decided about a topic and why - stop re-reading the same files in a new session - keep notes and code on your own disk - search Cyrillic notes without extra configuration ## Example prompts - Index this project and record in memory why we picked this caching approach - Search memory for what we decided about the migration scheme - Show the token savings with `server_info()` ## Similar - [REA](https://affpapa.org/en/nevibecode/mcp/rea.md) — MCP server · ★ 386989 - [GitHub](https://affpapa.org/en/nevibecode/mcp/github.md) — MCP server · ★ 33918 - [Netdata](https://affpapa.org/en/nevibecode/mcp/netdata.md) — MCP server · ★ 81115 - [browser-use](https://affpapa.org/en/nevibecode/mcp/browser-use.md) — MCP server · ★ 119160 - [Codebase Memory](https://affpapa.org/en/nevibecode/mcp/codebase-memory.md) — MCP server · ★ 47392 - [mcp-server](https://affpapa.org/en/nevibecode/mcp/mcp-server.md) — MCP server · ★ 43872 --- NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md