GitHub
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Beschreibung vom Entwickler (englisches Original)
Local-first AI identity for MCP coding tools. Lessons, decisions, and context you control.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
ENGRAM_MCP_STARTUP_SYNC, ENGRAM_TOOLS, PYTHONIOENCODINGDu brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"piia-engram": {
"command": "uvx",
"args": [
"piia-engram",
"--transport",
"stdio"
],
"env": {
"ENGRAM_MCP_STARTUP_SYNC": "your-value",
"ENGRAM_TOOLS": "your-value",
"PYTHONIOENCODING": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add piia-engram --env ENGRAM_MCP_STARTUP_SYNC=your-value --env ENGRAM_TOOLS=your-value --env PYTHONIOENCODING=your-value -- uvx piia-engram --transport stdioTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"piia-engram": {
"command": "uvx",
"args": [
"piia-engram",
"--transport",
"stdio"
],
"env": {
"ENGRAM_MCP_STARTUP_SYNC": "your-value",
"ENGRAM_TOOLS": "your-value",
"PYTHONIOENCODING": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"piia-engram": {
"type": "stdio",
"command": "uvx",
"args": [
"piia-engram",
"--transport",
"stdio"
],
"env": {
"ENGRAM_MCP_STARTUP_SYNC": "your-value",
"ENGRAM_TOOLS": "your-value",
"PYTHONIOENCODING": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
ENGRAM_MCP_STARTUP_SYNC envENGRAM_TOOLS envPYTHONIOENCODING envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 9. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto Patdolitse bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (4.27.0) kam vor 8 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: GitHub, Desktop Commander, Cloudflare MCP
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Tell AI once who you are, how you work, and what "good" means. Claude Code, Codex, Cursor, Windsurf, and other MCP-compatible tools can start from the same AI work identity layer — local files you own, no cloud account, no hidden memory you cannot inspect.
Install · See It in Action · Supported Tools · MCP Tools · FAQ
ENGLISH | 中文
Listed in:
Also listed in: awesome-agents · Awesome-MCP-ZH · mcpservers.org · Cursor Directory · ModelScope · PulseMCP
TL;DR: piia-engram is a local-first personal AI identity layer. It helps multiple coding agents start from the same understanding of you: your preferences, quality bar, lessons learned, decisions, and project context. It is not an agent memory database; it is the user-owned layer above your tools.
Why not just use native memory? Claude Code, Codex, Cursor, and Windsurf are adding their own memories and rules. Those are useful, but they are scoped to one tool or workspace. piia-engram gives you one portable identity layer above them: local files you own, AI-proposed knowledge you review, and context that can follow you across tools.
Trust model in four lines:
pip, keep the core store on your machine.~/.engram/ as JSON/Markdown.ENGRAM_APPROVAL=strict to gate every write. "Verified" means accepted by you or by that policy, not re-checked against your current code.Want proof? See the live cross-tool continuity proof — a memory written by Claude Code, read back by Codex through one local store — or the one-command reproducible code demo.
You → "Help me refactor this auth module"
AI → "What language? What framework? What's your testing preference?"
AI → "Based on your preference for pytest + 90% coverage, and your lesson about always separating auth middleware from business logic (from the March incident), here's my approach..."
And you never have to take that on faith — Memory Lens (engram preview --html) shows exactly what any AI caller would receive, and what governance withheld, before anything is sent:
*Above: a real report from a demo store — 4 items exposed; an unreviewed staging note and a lesson containing a credential are withheld, with the secret shown as [REDACTED].*
pip install piia-engram && engram setup
The wizard auto-detects your AI tools — Claude Code, Cursor, Codex, Claude Desktop — lists the exact config files it will touch, and writes the MCP connection after a one-keystroke confirm (every write is backed up first; decline and nothing changes). It previews your identity card, then you restart your configured tool; the first conversation can load your approved identity and long-term knowledge through startup or search tools. (full walkthrough ↓)
Ask your coding agent to install Engram and inspect the plan before applying:
pip install piia-engram
engram setup --non-interactive --json engram setup --non-interactive --apply engram doctor --json
Setup asks no questions. Use --clients cursor,codex to limit clients and --lang zh|en for output language (default en). Without --apply, plan mode writes nothing to the Engram store, home directory or client configs. Python itself may use the system temporary directory. Apply configures MCP connections with backups, preserves existing tool modes, and never imports memories, writes identity/knowledge, or approves proposals. Restart configured clients; exit code 1 means a manual step remains. See llms.txt for agent instructions and the CLI and JSON contract for details.
Evidence levels follow the agent client validation runbook: L0 = discovery, L1 = protocol access, L2 = read/search behavior, L3 = A/B behavior gain, L4 = cross-client continuity, L5 = reproducible public evidence.
| Tool | Integration | Evidence status |
|---|---|---|
| Claude Code | MCP over stdio | L4 partial continuity proof (Claude Code -> Codex) |
| Codex | MCP over stdio | L4 partial continuity proof (Claude Code -> Codex) |
| Cursor | MCP over stdio | L2 setup/read-search evidence path |
| Claude Desktop | MCP over stdio | L1/L2 setup path; client-specific evidence pending |
| Hermes | MCP over stdio | L4 controlled CLI marker continuity; desktop and broad benchmark claims unverified |
| OpenClaw | SOUL.md / MEMORY.md / USER.md import and export | L3 static file-bridge evidence (static snapshot A/B only; live agent behavior unverified) |
| ChatGPT / Gemini / Kimi | Markdown identity card fallback | Usable |
| Windsurf | MCP over stdio | Expected to work |
| GitHub Copilot | MCP over stdio | Expected to work |
| Cline | MCP over stdio | Expected to work |
| Roo Code | MCP over stdio | Expected to work |
| Amazon Q | MCP over stdio | Expected to work |
| Augment | MCP over stdio | Expected to work |
| Zed | MCP over stdio | Expected to work |
| Trae | MCP over stdio | Expected to work |
| Tencent CodeBuddy | MCP over stdio | Expected to work |
These are current repository facts from docs/public-facts.json. Public registries and package badges update only during release/publish.
| Current repo / development facts | |
|---|---|
| Version frame | v4.27.0 (verified 2026-11-01; check PyPI and GitHub Releases for the latest published package) |
| Supported AI tools | 16 (evidence level varies by client; see Supported Tools and the validation runbook) |
| MCP tools | 19 Core (loaded by default) + 40 Advanced (opt-in via ENGRAM_TOOLS=all) |
| Knowledge types | 3 (lessons, decisions, playbooks) |
| Test suite | Unit + integration; run pytest tests/ to verify |
Lines in core.py | 1770 (facade; domain logic now lives in focused mixins — see architecture.md) |
| PBKDF2 iterations | 600,000 (OWASP 2023+ floor; legacy 100k still decrypts) |
| Encryption | Optional field-level AES-256-GCM for supported profile fields; local files are plaintext JSON/Markdown by default |
| Cold-start time | < 100 ms typical (local JSON, no network) |
| Network calls by default | One anonymous usage ping a day (engram telemetry off or DO_NOT_TRACK=1 turns it off); the engram command also checks PyPI for a newer version at most once a day in interactive terminals, and engram doctor checks on each run (ENGRAM_NO_UPDATE_CHECK=1 turns it off); identity and knowledge tools make none, except the optional read_web_content; remote telemetry and feedback require separate explicit opt-in and send counts only (see privacy details) |
Your AI forgets you every time you switch tools or start a new chat. piia-engram fixes the handoff.
Every time you open a new chat window, switch from Claude Code to Codex, update your AI tool, or move into a different project, you're back to zero:
This happens because AI memory today is locked inside each platform. It belongs to the tool, not to you. The tool updates, resets, or gets replaced — and your context disappears with it.
piia-engram gives you a personal identity layer that lives on your machine, independent of any AI tool. You tell it once who you are, how you work, and what you've learned. MCP-compatible tools can read the same approved identity and long-term knowledge. New chat, new tool, new version — your identity stays portable.
piia-engram is not an agent memory database. Tools like Mem0, Zep, and Letta store task context and session history for AI agents. piia-engram stores *who you are as a person* — your identity, preferences, hard-won lessons, and key decisions. It's a different layer: not what happened in a task, but who is behind every task.
| Without piia-engram | With piia-engram |
|---|---|
| New chat window = start from zero | Configured conversations can load your approved identity and long-term knowledge |
| AI tool updates and your preferences vanish | Your identity lives on your machine, survives any update |
| Switching tools loses accumulated context | Claude Code, Codex, and Cursor read the same memory |
| Past mistakes get repeated | Lessons learned follow you across tools and sessions |
| Memory is locked inside one product | Data stays local, editable, and portable |
piia-engram is built for developers who use multiple AI coding tools and are tired of re-explaining themselves.
If you switch between Claude Code, Codex, and Cursor — your code standards, architecture decisions, and hard-won lessons reset every time. piia-engram makes eve
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