01
One corpus, every assistant
Claude Code, Codex, Gemini, Antigravity, goose, Cursor, Kimi and more read and write the same local memory over MCP. Switch tools mid-project and keep every hard-won detail.
The ship-log for your coding agents
Shared memory, skills and capabilities for every coding agent.
One private ship-log, one synchronized skill library, and one map of what every assistant can actually do. Captain Memo recalls what your agents learned, mirrors the skills they installed, and routes work to the AI that owns the right plugin or extension.
install
claude plugin marketplace add kalinbogatzevski/captain-memo
Cross-AI one corpus◆
Native capture as work happens◆
Virtual Skills one catalog◆
Virtual Capabilities one route map◆
No API key required◆
Fully local runs on Ollama◆
Linux · macOS · Windows
One command wires every AI coding tool on the machine. They all read and write one local corpus.
A shared library and capability map
Virtual Skills explain how. Virtual Capabilities show where.
Captain Memo mirrors the instructions your AIs know and safely publishes the plugins and extensions each runtime can execute. Every connected assistant can discover the best method, find the right owner, and delegate the work without copying secrets or pretending every CLI can run every tool.
Virtual Skills: reusable instructions
Skill discovery is auto by default. Edit or remove the original SKILL.md and its searchable, portable virtual copy updates with it.
Virtual Capabilities: safe delegation
Plugin discovery is also auto by default. Captain Memo publishes only sanitized names, operations and interfaces, then routes execution to the owning AI—never the manifest, credentials or command configuration.
See both in action
captain-memo skill list · captain-memo capability list
Native lifecycle capture
The memory arrives while the work is still happening.
On supported Codex, Gemini CLI and Kimi releases, Captain Memo installs native prompt, tool-result and turn-end hooks. Useful evidence reaches the same local observation pipeline immediately—not after a transcript reader eventually notices the session.
Native when proven
A session becomes native only after its first successful tool event reaches the worker. stats.capture.native shows the proven sessions by CLI.
Fallback without gaps
Older, disabled, untrusted or failed hook installs keep using the existing transcript and rollout readers automatically. Installation alone never switches fallback off.
How native capture works
Codex · Gemini CLI · Kimi · automatic compatibility
What a memory store turns into
Enough of it, and the pile has a shape.
Nothing here is tagged, foldered or curated into place. These are 144,159 embeddings from one working store, partitioned with no labels and no supervision — and then read back to see what the partition had found.
Beat one
Every note and captured observation becomes a vector. No schema, no tags, nothing decided in advance.
Beat two
k-means partitions them. 87% of the clusters it finds span more than one repository.
Beat three
Where the same fact was learned in separate sessions weeks apart, a model names it. Most candidates are declined.
Clusters
The structure already in the store: 477 centroids, and the three kinds of grouping nobody designed. Read the analysis →Dreaming
The offline pass that folds restatements and writes themes, grouped by what you recall together. How it decides →Recall
What the clusters are for: 1166 ms of exhaustive scan down to 47.5 ms, at recall@10 of 0.938. See the arithmetic →Logbook entries
What makes it different.
Not another cloud memory service. A local layer that every AI coding tool on your machine can share.
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No API key required
Summarize with the Claude, ChatGPT, or Google login you already have, or run it fully local on Ollama. Three of the summarizer backends need no key at all.
03
Local-first, and yours
The vector store and metadata live on your disk. Hybrid search (embeddings plus keyword), indefinite retention, and no cloud bill for remembering.
The voyage
Watch, remember, recall.
It runs quietly in the background. You never stop to manage it.
Watch
Captures each working session as structured observations: what changed, what you learned, what to reuse.
Remember
Indexes them into a hybrid search corpus, dedupes the noise, and keeps them for as long as you want.
Recall
Injects the relevant memory into every prompt, so your assistant starts already knowing the context.
The log never goes stale. Every session sharpens the next.
The ship's scribe
How your log gets written.
The summarizer is the scribe of the crew. After each stretch of work it reads what happened, the files you touched, the commands you ran, what you worked out, and writes it up as one short, structured log entry. Those entries are what make your past work searchable later.
Runs on a login you already have
Point it at the Claude, ChatGPT, or Google account you already sign in with, or a local model on Ollama. Three of the choices need no API key at all. It works in the background, a batch at a time, so it never slows a prompt down.
You choose the scribe, and only one sails
Pick a single summarizer when you install. Only one is ever active. See who is on watch any time with captain-memo stats, which names the provider and whether it is actually writing entries.
If the scribe steps away
Nothing is lost. Your session waits safe in a durable queue. A passing outage retries on its own with no penalty; a missing login simply pauses the writing until you sort it out, then the queued work gets written up. And the rest of your memory, watched files, saved notes, and search, keeps working the whole time.
The hold
How memory is stored, and found.
Everything you keep is indexed two ways at once, so recall works whether you remember the exact words or only the gist.
Hybrid search
Meaning-based vector search and plain keyword search, fused into one ranking, with a gentle tilt toward recent work so today's context surfaces first. Multilingual too: your non-English notes are just as findable.
Your embedder, your call
A tiny hosted model by default (around $0.30 a year of usage), or run it fully local and offline, or point it at Ollama or any /v1/embeddings endpoint. Indefinite retention, and no cloud database to rent.
Dreaming — what happens while you're not looking
A corpus that only ever grows eventually crowds out the memories you want. Dreaming folds related observations into a single higher-level theme, and it groups them by what you actually recall together — not merely by what shares vocabulary, which just yields groups that use the same words. The originals are archived, never deleted. It runs on your machine, only while you are away from it, and every change is reversible with one command.
The name is Anthropic's — Claude Managed Agents shipped Dreams in May 2026, a cloud pass that re-reads an agent's transcripts to rebuild its memory store. Captain Memo does the same job locally, and works out what belongs together from co-retrieval rather than by re-reading the text. How dreaming works →
The fleet
Works with what you already use.
Twelve assistants share one memory through Captain Memo's MCP server and a portable skill. One command wires each of them.
Claude Code
Codex
Gemini CLI
Antigravity
goose
Cursor
Kimi
opencode
Mistral Vibe
VS Code / Copilot
JetBrains
Claude Desktop
Ollama
LM Studio
any /v1 endpoint
The last three run the summarizer and embedder locally, so a machine with no Claude, ChatGPT, or Google account can still remember, entirely offline.
The captain's manual
Commands and tools.
A handful of commands run it from your terminal. Your assistants get a matching set of tools they call on their own.
In your terminal
Run captain-memo help for the full list.
- captain-memo install
- Interactive setup: embedder, worker, plugin, and your summarizer.
- captain-memo connect <tool>
- Wire another assistant (Codex, Gemini, Cursor, opencode and more) to the shared memory.
- captain-memo doctor
- Health probe across the embedder, worker, and plugin. Your first stop if anything looks off.
- captain-memo stats · top
- Corpus size and the active summarizer.
topis a live dashboard: sort, filter, drill, an AI-sources chart, and a built-in glossary (?) — see the full stats glossary. - captain-memo upgrade
- Bring the corpus to the current format, end to end (reindex plus compact). Safe to re-run.
- captain-memo remember "..."
- Save a durable note by hand, the things you never want it to forget.
- captain-memo skill list
- Browse every synchronized virtual skill, optionally filtered by its source AI.
- captain-memo backup · restore
- A portable archive: move your whole memory to another machine.
What your assistant can do
Called automatically over MCP. You never invoke them by hand.
- search_memory
- Find the relevant notes and watched files in your corpus.
- search_observations
- Search the auto-captured log of what you did in past sessions.
- search_all
- One search across everything at once: notes, session log, and skills.
- list_skills · recommend_skills
- Browse the skill catalog or find the few installed skills relevant to the task.
- load_skill
- Load the complete advisory instructions after choosing a virtual skill.
- remember
- Save something worth keeping straight into curated memory.
- get_full
- Pull up a whole document when a snippet is not enough.
- stats · status
- Report what memory it can see and whether the worker is healthy.
You stay the captain
Your memory never leaves without orders.
The whole corpus, every vector and every note, lives on your own disk. Captain Memo logs the voyage; you decide what, if anything, is ever sent anywhere.
Local by default
Nothing is uploaded for storage. The only things that ever leave are the calls to the summarizer and embedder you chose, and only for the moment they run.
Fully offline if you want
Run both the summarizer and the embedder on a local model, and nothing at all leaves the machine. No account, no key, no cloud, no exceptions.
Before you sail
Questions from the dock.
The things people ask before they hoist the plugin.
Do I need a Claude subscription?
No. It works with Codex, Gemini, Cursor and more, and the summarizer can run on your ChatGPT or Google login, or fully local on Ollama. A machine with no Claude at all still remembers.
Will it slow down my prompts?
No. The writing happens in the background between prompts, a batch at a time. You never wait on it, and a whole session becomes a single log entry.
Where does my data live?
On your own disk, under your home directory. There is no cloud database, and nothing is uploaded for storage.
Can I run it completely offline?
Yes. Choose the local embedder and a local summarizer model, and Captain Memo runs with no network at all.
Is it really free?
Yes, open source under Apache-2.0. The optional hosted embedder runs about $0.30 a year; keep everything local and it costs nothing.
How is it different from a cloud memory service?
It is local, it is shared across all your AI tools instead of locked to one, and it is yours. No vendor account, no lock-in, no per-call bill for remembering.
What if the summarizer stops working?
Nothing is lost. Your sessions wait in a durable queue and get written up once it is back. An outage retries with no penalty, and the rest of your memory keeps working meanwhile.
Cast off
Running in under a minute.
Installs from the Claude Code marketplace. No account, no config to start.
- Add the plugin. Run the install command, then fully restart Claude Code.
- Pick a summarizer (optional).
captain-memo installlets you choose Claude, Codex, Gemini, or a local Ollama model. - That's it. Memory is captured, indexed, and injected from your very next prompt. Check it with
captain-memo stats.
Runs natively on Linux (systemd --user), macOS (a per-user launchd LaunchAgent — no root) and Windows x64 (a per-user Scheduled Task — no WSL, no admin). One CLI, three supervisors; the wizard picks the right one and checks its prerequisites before touching anything. On macOS, brew install sqlite first — Apple's own SQLite cannot load the vector extension.
quick start
claude plugin marketplace add kalinbogatzevski/captain-memocaptain-memo doctor