Finance Toolkit
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
Beschreibung vom Entwickler (englisches Original)
Read-only MCP access to a local append-only evidence ledger for AI agent sessions.
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.
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
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.
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.
Diese 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 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto Liyuan1992 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 (0.7.1) kam vor 2 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB auf deinem Computer.
In derselben Kategorie: Finance Toolkit, SolidInvoice, Korea Tax Calculator
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
Create and send invoices and quotes, manage clients, and track payments in SolidInvoice.
Korean tax calculation and tax-audit judgment MCP: 96 tools with statutory citations.
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.
English | 简体中文
rawmem is a tiny local-first evidence ledger for AI and human workflows.
The idea is deliberately small:
Store now, understand later.
AI memory systems often start by summarizing. rawmem starts one layer lower: append-only raw evidence. A chat turn, a 2px UI tweak, a bug fix, a command run, a git snapshot, a browser clip, or a coding-agent completion can all become the same kind of local event.
The hard boundary is simple: capture is not recall. The ledger is a source layer. Review, filtering, MemoryDSL conversion, preference mining, and project rules can be derived later.
Small facts look noisy alone. Repeated across time and projects, they become patterns:
Disk is cheap. Missing history is expensive.
New to programming? Choose the Windows app (EXE). An EXE is a Windows program you open by double-clicking. Running it requires no Python installation or terminal commands.
| Who it is for | Choose | Requirements |
|---|---|---|
| Windows users who want a graphical app | Windows EXE preview | A built rawmem.exe; no Python required |
| Developers who want commands or integrations | Python CLI | Python 3.10+ and Git for the source installation below |
Choose one approach; you do not need both. There is currently no downloadable release of the new EXE preview. A developer must build it from source first. Users unfamiliar with programming can wait for an EXE release instead of following the Python commands below.
Once you have a built rawmem.exe, double-click it, choose a storage folder, decide whether to start at logon, and click to begin recording. Browser saving requires the optional extension. See Windows recorder for setup and build instructions. This preview is unsigned and the extension still requires manual developer-mode installation.
EXE users can skip this section. With Python 3.10+ and Git installed, run these commands in PowerShell:
git clone https://github.com/Liyuan1992/rawmem.git
cd rawmem python -m pip install --user -e .
The core runtime has no third-party dependencies. DeepSeek Harness compressed session capture and the MCP server are optional extras:
python -m pip install --user -e ".[deepseek-harness,mcp]"
To install the published v0.7.1 wheel without cloning the repository:
python -m pip install "rawmem[deepseek-harness,mcp] @ https://github.com/Liyuan1992/rawmem/releases/download/v0.7.1/rawmem-0.7.1-py3-none-any.whl"
Make sure the user Scripts directory (e.g. %APPDATA%\Python\Python312\Scripts) is on PATH so rawmem works from any directory.
rawmem setup --global --install-startup --dry-run # inspect first; writes nothing
rawmem setup --global --yes # global config + git hooks for all repos rawmem setup --install-startup --yes # run the daemon headless at every logon rawmem setup --start-daemon # start it right now rawmem config --show-browser-token # paste into the browser extension options rawmem doctor # verify the complete installation
After this the daemon passively tails Claude Code, Codex, and Cursor sessions, tails PowerShell history, watches configured directories, and serves the browser-capture endpoint — with zero per-event action from you. Clipboard polling is available but disabled by default; enable it explicitly in config or with rawmem config --include-clipboard. The guiding principle is passive over self-report: evidence is pulled from logs other tools already write, not pushed by agents remembering to report back.
See docs/SETUP.md for the full setup matrix and the browser extension.
For DeepSeek Harness capture plus bounded read-only MCP access, see docs/DEEPSEEK_HARNESS.md.
Background capture (the primary path):
rawmem daemon # run all background surfaces in one process
rawmem daemon --status # task counters, errors, last run times rawmem doctor # config, storage, daemon, token, startup, hooks, events rawmem doctor --strict # warnings also produce a nonzero exit code rawmem sync # one manual tailer pass rawmem sync --backfill # first run: also ingest existing history rawmem config --disable-clipboard rawmem config --rotate-browser-token
Preview or remove integrations:
rawmem setup --global --install-startup --dry-run
rawmem uninstall --dry-run rawmem uninstall # disables integrations; keeps ~/.rawmem rawmem uninstall --remove-home --yes # also deletes the ledger and local state
Inspect the ledger:
rawmem tail --limit 10
rawmem tail --source claude-code --limit 5 rawmem tail --project rawmem --type agent_user_turn --json rawmem verify --json rawmem export --cursor-file .rawmem\consumer-cursor.json --limit 100 rawmem seal --yes --json # unchanged read-only archive + linked active ledger rawmem archives --json # metadata-only derived archive registry rawmem export --archive .rawmem\archives\old.jsonl # explicit; metadata-only default
rawmem export uses the stable rawmem.cursor.v1 contract and never needs to load the whole ledger. Cursors bind to a ledger identity plus a byte offset and boundary hash, so truncation, replacement, or rotation is reported explicitly instead of silently skipping or duplicating evidence. See docs/LEDGER_PROTOCOL.md.
rawmem verify is strictly read-only: it never creates or refreshes lock/state sidecars. rawmem seal keeps historical bytes unchanged, records the full verification report and every accepted previous_hash_mismatch, marks the old ledger ReadOnly on Windows, and creates a chain-complete active ledger at the same configured path. Archive reads require --archive; they hash the complete archive before returning results, default to a body-free metadata projection, and surface recorded integrity warnings.
Manual and scripted capture:
rawmem capture --source manual --type note --text "First rawmem event"
"The button should be 2px larger." | rawmem capture --source clipboard --type ui_feedback --stdin rawmem ingest --file event.json "Selected page text" | rawmem clip --stdin --url "https://example.com" rawmem run --source terminal -- python --version rawmem git-snapshot
Capture preserves complete supported text without a character cap, including when old configurations still contain max_chars. Source batch sizes are processing budgets and never split complete records. Browser capture saves only the loaded document on an explicit click; it does not fetch hidden history.
| Surface | How | What lands in the ledger |
|---|---|---|
| Claude Code sessions | daemon tailer (zero friction) | user/assistant turns, project, session, branch |
| Codex sessions | daemon tailer (zero friction) | user/assistant turns, project, session |
| Cursor agent transcripts | daemon tailer (zero friction) | user/assistant turns, workspace, session |
| DeepSeek Harness sessions | opt-in daemon tailer (zero friction after setup) | direct user/model turns; tool name/id/status metadata only |
| WorkBuddy local history | opt-in daemon tailer (desktop setup enables it) | 5.1-style JSONL message text and source identity |
| OpenClaw local history | opt-in daemon tailer (desktop setup enables it) | legacy JSONL and new SQLite transcript messages; shared identity dedupe |
| Shell commands | daemon tailer of PSReadLine history | every completed command line |
| Clipboard | daemon poller (deduped, opt-in) | clipboard text changes |
| Git lifecycle, all repos | setup --global --yes core.hooksPath hooks | commit/checkout/merge/rewrite/push snapshots |
| File changes | daemon watcher | batched created/modified/deleted paths |
| Browser pages | MV3 extension (extension/) + token-protected localhost endpoint | selection or page text, title, URL |
| Any adapter/tool | ingest / POST /capture | JSON event payloads |
| Manual notes | capture / clip / run | raw text, tags, artifacts, command results |
By default, events are written to:
~/.rawmem/events.jsonl
Use --local to write to the current project's private ledger:
.rawmem/events.jsonl
Use --ledger or RAWMEM_LEDGER for an explicit ledger path.
Capture policy is configured under privacy in ~/.rawmem/config.json. Optional project/path allowlists fail closed, common secret shapes are redacted before append, and artifacts default to metadata references rather than embedded content. Daemon status and rawmem doctor expose source coverage, skipped events, redactions, and cursor health without printing captured text.
.rawmem/ is ignored by Git because raw evidence can contain private text, paths, command output, and local work context.
Each line is JSON:
{
"schema": "rawmem.event.v1", "event_id": "evt_...", "ts": "2026-07-09T00:00:00Z", "source": "codex", "event_type": "task_note", "project": "rawmem", "cwd": "/workspace/fictional-rawmem", "summary": "User asked for a local-first raw evidence ledger.", "raw_text": "User asked for a local-first raw evidence ledger.", "tags": [], "artifacts": [], "payload": {}, "privacy": { "scope": "local_only", "review_required": true }, "previous_hash": null, "content_hash": "..." }
The previous_hash / content_hash chain is a lightweight tamper-evidence mechanism. It is not a security boundary, but it makes accidental rewrites more visible.
rawmem should not chase every AI tool with one giant integration. The stable piece is the ledger. Capture adapters can be small and optional:
All adapters should emit the same event schema.
MCP is a query adapter, not a promotion path. rawmem-mcp exposes only path-free status, bounded recent events, and archive metadata. Summary access is the default; raw bodies require an explicit read:full scope.
~/.rawmem/config.json.--yes.rawmem uninstall preserves captured data unless --remove-home --yes is explicit.See PRIVACY.md and SECURITY.md before enabling background capture on a daily driver machine.
$env:PYTHONPATH = "src"
python -m unittest discover -s tests python scripts/open_source_audit.py