MemoryThreads
FreeNot checkedPersistent, searchable conversation memory shared across Claude Code and Codex, enabling cross-session recall and thread continuity via hybrid BM25 and vector s
About
Persistent, searchable conversation memory shared across Claude Code and Codex, enabling cross-session recall and thread continuity via hybrid BM25 and vector search.
README
Persistent, searchable conversation memory shared across Claude Code and Codex.
MemoryThreads is a local MCP server that auto-captures every conversation turn from both Claude Code and OpenAI Codex into one SQLite database, then makes that history instantly searchable from any future session - hybrid BM25 (FTS5) + vector (sqlite-vec) recall, with cross-platform thread continuity. Start work in Claude Code, continue it in Codex, and either side can recall the full shared history.
No cloud, no account - everything lives in ~/.claude/memory-server/ on your machine.
Install (one command)
Prerequisites: Node.js 18.18+, and an OpenAI API key (used only for local embeddings).
git clone https://github.com/v3velev/memorythreads ~/.claude/memory-server
cd ~/.claude/memory-server && ./install.sh
The installer prompts for your OpenAI key (or reads OPENAI_API_KEY from your env), then does everything:
- installs npm dependencies and writes
.env - registers the
memoryMCP server for Claude Code (claude mcp add) and Codex (~/.codex/config.toml) - installs the capture/recall hooks into
~/.claude/settings.jsonand~/.codex/hooks.json - installs the
/mt-*slash commands - adds the Memory block to your
~/.claude/CLAUDE.md(and~/.codex/AGENTS.md) so your agent uses recall automatically - starts the background worker (launchd on macOS) that parses + embeds transcripts
It is idempotent - safe to re-run. After it finishes, restart Claude Code / Codex.
Install with your AI agent
You can also just hand the repo to your own Claude Code and let it install itself. Paste this:
Install the MemoryThreads memory server from https://github.com/v3velev/memorythreads - clone it to
~/.claude/memory-server, run./install.sh, and give it my OpenAI API key when it asks. Then restart so the MCP server and hooks load.
What gets added to your CLAUDE.md
The installer inserts this block (between <!-- memorythreads:start/end --> markers, so re-running never duplicates it):
## Memory (MemoryThreads)
- Conversation turns are auto-saved to SQLite and searchable across all past sessions (both Claude Code and Codex).
- Before guessing or asking the user about an unfamiliar term, file, project, or past decision, call `recall_context(query, include_threads=true)` first.
- `search_docs(query)` searches ingested reference docs.
- Bookmark the current session with `/mt-save <name>`; list and resume bookmarks with `mt launch`.
Full manual steps and Linux notes are in SETUP.md.
Why
LLM coding sessions are stateless - close the terminal and the context is gone. MemoryThreads fixes that:
- Never re-explain.
recall_context("that auth bug from last week")pulls the actual prior turns. - Cross-tool. Claude Code and Codex write into and read from the same memory, so switching tools never loses the thread.
- Automatic. Hooks capture turns on every session; you don't manage it.
- Fast + private. Local SQLite, FTS5 + sqlite-vec. Your conversations never leave your machine.
How it works
Claude Code ─┐ ┌─ recall_context / search_docs
├─ hooks ─► jobs queue ─► worker.js ─► SQLite ◄─┤ (MCP tools)
Codex ─┘ (capture) (parse + embed) └─ mt launch (resume)
- Capture. Session hooks (Stop, PreCompact, UserPromptSubmit) queue each session's transcript for ingestion. A launchd file-watcher (
incremental-sync.js) also ingests Claude Code turns continuously. - Parse + embed.
worker.jsparses transcripts (dual-format: Claude Code JSONL and Codex rollout JSONL viatranscript-parser.js), stores turns + threads, and embeds each turn (OpenAItext-embedding-3-small, 1536-dim) into a sqlite-vec table. - Recall. The MCP server (
server.js) exposesrecall_context, which runs hybrid BM25 + cosine search over turns/threads and returns the matches to the model. - Continuity. A
canonical_thread_idlinks a Claude Code stream and a Codex stream into one logical MemoryThread, so continuation works across both tools without sharing native session files.
MCP tools
| Tool | Purpose |
|---|---|
recall_context(query, resolution=0, include_threads) |
Hybrid BM25 + vector search. resolution 0 = raw turns (default), 1 = full threads, 2 = thread key-exchanges. |
search_docs(query) |
FTS5 search over ingested reference docs. |
ingest_doc(source, tags?, title?) |
Add a reference doc (URL, llms.txt, or local file). |
list_docs / delete_doc |
Manage ingested docs. |
save_thread(name, ...) |
Bookmark the current session as a named MemoryThread. |
list_threads / activate_thread / delete_thread |
Manage and resume bookmarks. |
Slash commands & CLI
/mt-save <name>,/mt-list,/mt-delete <name>,/mt-doc-ingest <source>mt launch- interactive picker to resume a saved thread (mt launch tmuxfor a tmux session)mt browse- TUI to browse/filter all threadsmt status- DB stats, worker status, recent activitymt doctor- full health check (worker, job backlog, embeddings, hooks + MCP wiring). Run this if memory seems stale - it surfaces silent failures. The session-start hook also warns automatically if the ingest backlog gets stuck.
Data model
One SQLite DB (data/memory.db). Core tables: threads, turns, turns_fts (FTS5), turn_embeddings (sqlite-vec), plus saved_threads, active_memory_threads, docs, tool_uses, summaries, recovery_buffer, and the worker jobs queue. Full DDL in SCHEMA.md.
Recall operates directly over conversation turns and threads - there is no extracted-knowledge layer.
Setup
See SETUP.md for the full guide. In short:
npm install- Put
OPENAI_API_KEY=...in.env(gitignored). - Register the MCP server:
claude mcp add --scope user memory node ~/.claude/memory-server/server.js(and the[mcp_servers.memory]block in~/.codex/config.tomlfor Codex). - Add the hooks block to
~/.claude/settings.jsonand~/.codex/hooks.json. - Start the worker via the launchd watchdog.
Hooks
| Event | Script | Role |
|---|---|---|
SessionStart |
session-start-cold.sh / session-start-compact.sh |
Status line; compaction recovery |
UserPromptSubmit |
user-prompt-submit.cjs |
Inject relevant prior turns + active-thread context |
PreCompact |
pre-compact.sh |
Snapshot recent turns to recovery_buffer before compaction |
Stop |
stop.cjs |
Queue the session transcript for ingestion |
The same hook scripts serve both Claude Code (settings.json) and Codex (hooks.json).
Tech stack
Node.js (ES modules) · better-sqlite3 · sqlite-vec · OpenAI embeddings · @modelcontextprotocol/sdk · SQLite FTS5.
Privacy
All data is local. .env (your API key) and data/ (the DB) are gitignored and never committed.
Install MemoryThreads in Claude Desktop, Claude Code & Cursor
unyly install memorythreadsInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add memorythreads -- npx -y github:v3velev/memorythreadsFAQ
Is MemoryThreads MCP free?
Yes, MemoryThreads MCP is free — one-click install via Unyly at no cost.
Does MemoryThreads need an API key?
No, MemoryThreads runs without API keys or environment variables.
Is MemoryThreads hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install MemoryThreads in Claude Desktop, Claude Code or Cursor?
Open MemoryThreads on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
Related MCPs
GitHub
PRs, issues, code search, CI status
by GitHubFilesystem
Secure file operations with configurable access controls.
Memory
Knowledge graph-based persistent memory system.
Template MCP Server
A CLI tool to create a new Model Context Protocol server project with TypeScript support, dual transport options, and an extensible structure
by mcpdotdirectCompare MemoryThreads with
Not sure what to pick?
Find your stack in 60 seconds
Author?
Embed badge for your README
Browse similar
All development MCPs
