Open source · local-first · MCP

Finally, every AI knows you.

Persnally learns who you are from your AI history — your chats, your code, your decisions — and serves it to every AI you use. On your machine. Yours.

Star on GitHub
Engraving of a head in profile overlaid with a proportional measuring gridwhat you're intolocal-first systems · weight 0.95how you decide“hand-roll it, not a new dep”how you writeterse · lowercase · no emojiyour conventionspnpm, never npmwhy it knowslearned from event #412 · deletable
Fig. 1 — a model of youyour history · your machine
ClaudeCursorCodexGeminiCopilotZedWindsurfClaudeCursorCodexGeminiCopilotZedWindsurf

One command connects them all · ChatGPT history imports too

01The problem

You explain yourself. Again. And again.

ChatGPT doesn't know what you told Claude. Your coding agent relearns your stack every session. Each tool meets you as a stranger — and the vendors can't fix it, because their business is keeping you inside their walls.

Claude sees

ChatGPT sees

Cursor sees

Fig. 2 — one you. Each tool sees only its slice.
To Claude said before

My stack: TypeScript, Next.js, Tailwind.

02How it works

Your context, in every tool you touch.

I.Import

Import your history

One command finds your Claude & ChatGPT exports, your Claude Code sessions, and your git repos, and reads them.

the press — your history, taken in

$ persnally import

  • Claude & ChatGPT exports
  • Claude Code sessions
  • git repos
II.Learn · local

It learns, on your machine

A local daemon turns that history into an evidence-linked model of you — never our cloud.

the compositors — studied, locally

building your model…

  • ships the smallest design
  • prefers SQLite
  • guards user trust

on your machine

III.Serve · MCP

Every AI reads it

Over MCP — the protocol your tools already speak. Claude Code pulls it in the moment a session starts; Claude, Cursor, and your agents read it whenever they need you.

the messenger — served to every tool

Claude · session started

↳ loaded your context

persnally_context 2ms

03See it

Not a metaphor. The actual dashboard.

Every engraving on this page is standing in for something real. Below is the real thing, live — the same page served at localhost:4983 on your machine. Scroll it, click a node, judge an answer. It's running in preview mode: sample data, nothing writable, nothing sent anywhere.

persnally — your context engine
04Answers, not just recall

The only context engine your AI can ask.

Other tools store facts. Persnally answers what you'd do — with a confidence score, deferring to you when the evidence is thin.

It answers, or it defers

Your agent asks Persnally instead of interrupting you. Below its confidence bar, it sends the agent back to you — never a made-up answer.

the evidence, weighed — below the bar, it defers to you

persnally_ask “tests before I merge?”

↳ yes — you demand proof before merge; add e2e on the changed paths.

confidence 0.92 · 3 evidence events

Correct it once, it sticks

Tell it it's wrong and the correction becomes authoritative — it outranks everything inferred, and the wrong answer never comes back.

written in your own hand — outranks everything inferred

persnally correct “I use pnpm, not npm”

↳ recorded — authoritative.

every future answer respects it

See the difference

Same prompt — “write a Slack message telling my team the deploy went out” — asked of a blank AI and an AI that read your Persnally:

Generic AI

🚀 Deploy is live! Just pushed the latest changes to production. Everything looks good so far — let me know if you spot anything unexpected.

AI + Persnally

deploy is out. watching sentry/logs for the next hour, will confirm clean or flag issues here.

Terse, lowercase, no emoji, and it knew to watch Sentry — because that's how you actually work. Not configured; learned.

05Under the hood

More than memory. An engine.

Structured events, derived views, a walkable provenance graph — decay-aware, and entirely your own.

Cross-vendor · MCP

One context, every tool reads it.

the well — one source, every tool draws
Claudepersnally_context
Cursorpersnally_context
Claude Codepersnally_ask
your agentpersnally_search

speaks MCP — adopted by every major AI

Provenance

Every claim cites its evidence.

the specimen — every part numbered, keyed to its source

Guards user trust as non-negotiable.

↳ why does it think this? 3 events

  • #128 · imported 142 Claude conversations
  • #412 · vetoed telemetry without consent
  • #087 · chose local-first storage

3 events · 0 guesses · each one deletable

Per-client scopes

Decide exactly what each AI can see.

the card table — each player sees only its own hand
Claudeallowed
Cursorallowed
Claude Codescoped
agentsscoped
06How it compares

Everyone remembers. Persnally answers.

No one else answers what you'd do, learns when you correct it, and lets you verify all of it on your own machine.

CapabilityPersnallyclaude-memMem0 · SupermemoryUnabyss · cloud vaults
Your AI can ask it — answer with a confidence score, defers when unsure
Learns when you correct it — the correction outranks everything inferred
Synthesizes a model of you — taste, voice, how you decide
Local plaintext on your machine + source you can audit
Reads your chat exports + git history

has it · partial · no. Verified against each product's own docs and repos, July 2026.

07Your data, your rules

A context engine you can actually trust.

Trust isn't a privacy policy here — it's the architecture. Not promises; properties you can check.

Local-first

Your context lives in ~/.persnally — not our cloud, not any vendor's silo.

~/.persnally

  • persnally.db
  • config.json

stays on your machine, never our cloud

Truly deletable

Forget a topic and everything derived from it is erased, then rebuilt.

$ persnally forget “rust”

  • ✓ 18 events erased
  • ✓ derived views rebuilt

no tombstones · no residue

Provenance-complete

“Why does it think this?” is a real lookup, never a guess.

↳ why “guards user trust”?

  • #412 · vetoed telemetry
  • #087 · chose local-first
  • #203 · removed analytics

3 events · 0 guesses

Source-available

Read the engine, audit the claims, run it yourself. The schema and MCP interface are an open spec.

No accountBring your own keysWorks offlineOpen spec
08The difference

Engraving of an armillary sphere — a measured model of a world
Fig. 3 — the model of you, measured.

Every AI knows you. And it's yours.

Every other memory tool

“a place to store facts about you”

  • A database of you — you save, you search, you retrieve
  • Recalls facts; can't answer what you'd decide
  • Correct it? Delete a memory, at best
  • A black box — it can't tell you why

Persnally

your own context engine

  • A model of you your AI can ask — with a confidence score
  • Answers what you'd do; defers to you when unsure
  • Correct it once and it sticks — outranks everything inferred
  • Every claim cites its evidence — local, auditable, deletable
№ 09 — Pricing

The engine is free. Forever.

Free · Pro · Teams later

Everything that touches your data runs on your machine, free. Pro adds cloud services on top — and tells you exactly which of them can see what.

Free

$0 forever

the loom — the whole engine, at home
  • The full engine — import, learn, synthesize your profile
  • Serve your context to every AI over MCP
  • The dashboard: inspect, audit provenance, delete
  • Bring your own key, or run fully local with Ollama

Pro

Coming soon

$6 / month · billed annually · founding price

the key — yours alone · backup & relay stay ciphertext
  • Encrypted backup & restore of your accumulated self — ciphertext, we hold no key
  • Agent relay — your phone and cloud agents reach your context, end-to-end encrypted
  • Zero-setup inference — no API key needed (fair-use). Processed in the clear, never stored
  • Reflection reports — what changed about you, over time

What the cloud can and can't see

Backup and agent relay: ciphertext.
Encrypted on your machine with a key that never leaves it. We can't read them — not because we promise not to, but because we don't hold the key.
Zero-setup inference: plaintext, in transit only.
Running a model over your context means your text reaches our compute in the clear. There is no end-to-end encrypted way to do inference — that's arithmetic, not policy. So it's opt-in, we never store it, it never joins a training set, and the client that sends it is source-available so you can check what leaves.
Don't want that? Then don't buy it.
The free engine uses your own key, or a local model through Ollama, and never touches our servers at all. Everything that makes Persnally yours works without us.

The line we won't cross: the cloud may carry ciphertext and run jobs you asked for. It never becomes the place your context lives.

Privacy is never the paid tier. The local engine, the dashboard, and deletion stay free — Pro is convenience on top, not a wall around your own data.

10Five minutes to your mirror

Install, and see yourself.

One command finds your exports, reads your repos, synthesizes a profile, connects your AI clients, and opens the dashboard.

Engraving of a woman studying her own reflection in a hand-mirror, an eagle at her side
Fig. 4 — the mirror. It shows you what it learned.
npm i -g persnally && persnally setup

Paste in your terminal.

macOS · Linux · Windows · Node 20+ · background autostart on macOS & Linux · bring your own key, or run fully local with Ollama