Local memory for AI agents. One SQLite file on your machine β no cloud, no account.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Your AI assistant forgets you after every chat.
KEPTA remembers β on your own computer, in one file.
Open source Β· no cloud Β· no account Β· no subscription
SQLite Β· hybrid retrieval Β· knowledge graph Β· MCP
English Β· π©πͺ Deutsch

A full pass through the app: search, the editor with type and validity, creating a note, the trash with restore, the knowledge graph and its time slider, the chat cockpit, the MCP endpoints, the command palette and the theme switch. Recorded from version 2.6.16 on invented demo data β the Onyx interface.
| Index & hybrid search | Knowledge graph |
|---|---|
![]() | ![]() |
| Editor β type, validity, confidence | Setup β topics & starter pack |
![]() | ![]() |
Recorded from version 2.6.16 β the Onyx interface β on a demo corpus. No real data: every entry was made up for these shots. Note that the graph was rebuilt in 2.7.0 (unbounded canvas, collision, degree-weighted links); the shot above still shows the old rendering.

The time slider answers a question most note apps cannot: what did I know back then? Every memory carries a validity window, so the graph can be replayed. The dimmed nodes are not deleted β they simply were not true yet.
The problem. You use ChatGPT, Claude or something similar. You explain your project, your client, the way you like things done. The next day you open a fresh chat and it knows none of it. So you explain it again. And again.
What KEPTA is. A small program that runs on your own computer and remembers those things for you. Your assistant can look them up and write new ones back by itself. Nothing is sent anywhere β the notes live in a single file on your machine, like a document.
What that looks like on an ordinary day. You tell Claude to remember that your client bills quarterly. Two weeks later, in a brand-new chat, you ask about the invoice and it already knows. You drop a PDF into a folder and your assistant can quote from it. You move house, and the old address stops coming back.
Is it for you?
To use the app β no. Download the file for your system, open it, done. It is an ordinary window: a list, a search box, a settings page. The section Which file do I need? tells you exactly which one to take.
To connect it to Claude Desktop or Cursor β a little. You paste one short block of text into one configuration file. The block is ready to copy under Settings β MCP / API. If you have never edited such a file, this is the single step worth setting aside ten minutes for.
For the smarter search β optional. KEPTA searches perfectly well out of the box. Install Ollama β one free download β and it will additionally find notes that mean the same thing in different words.
| Word | What it means here |
|---|---|
| Agent | An AI program that can use tools instead of only answering β Claude Desktop or Cursor, for instance. |
| MCP | An agreed language for such programs to talk to tools. KEPTA speaks it, so those assistants can read and write your notes. |
| SQLite | A database that is simply one file on your disk. Nothing to run, nothing to log into; you can copy it like a photo. |
| Embedding / vector | Text turned into numbers, so a computer can tell that "car workshop" and "garage" mean nearly the same thing. |
| BM25 / full text | Classic keyword search: it finds the words you actually typed. |
| Knowledge graph | Your notes linked to one another, like [[links]] in a wiki. |
| RRF | The formula that merges the three searches above into one ranking. |
| Local-first | Everything happens on your machine. No upload, no account, no subscription. |
| Open source / MIT | The whole source code is public and free to use. You can read what it does instead of taking my word for it. |
ollama pull nomic-embed-text has run. Without an embedding model, search stays lexical and still works.
Measured caveat, September 2026: that example works in English and does not work in German. On a four-note check (npm run embed:sprachtest) the default model answers 4 of 4 English paraphrase questions and 1 of 4 of the same questions translated into German. The implementation is not at fault β normalised cosine, 768 dimensions β the default model is English-centric. If your notes are German, expect lexical search to carry most of the weight until you switch to a multilingual model such as bge-m3.[[wiki links]] become graph edges.~/.kepta/. MIT licensed, no account.POST /mcp (protocol 2026-07-28, 8 tools), HTTP API, npm run eval (Hit@1 62 %) and npm run ablation (what each retrieval leg contributes).No service in between, no account, no telemetry. The server binds to 127.0.0.1 unless you set KEPTA_HOST yourself. Your memories are stored only in that SQLite file β there is no server of mine for them to reach. The one path where data does leave is the app's optional chat: if you enter a key for OpenAI, Anthropic or another provider, what you send that provider goes to them. It is off until you add a key, and the memory store is never synced anywhere.

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