Finance Toolkit
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
Beschreibung vom Entwickler (englisches Original)
Verifiable cognition: prove a session ledger is tamper-evident; audit & import any agent's logs.
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.
KORG_JOURNAL_PATH, KORG_LEDGER_HMAC_KEYDu 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": {
"korg-ledger": {
"command": "uvx",
"args": [
"korgex"
],
"env": {
"KORG_JOURNAL_PATH": "your-value",
"KORG_LEDGER_HMAC_KEY": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add korg-ledger --env KORG_JOURNAL_PATH=your-value --env KORG_LEDGER_HMAC_KEY=your-value -- uvx korgexTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"korg-ledger": {
"command": "uvx",
"args": [
"korgex"
],
"env": {
"KORG_JOURNAL_PATH": "your-value",
"KORG_LEDGER_HMAC_KEY": "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": {
"korg-ledger": {
"type": "stdio",
"command": "uvx",
"args": [
"korgex"
],
"env": {
"KORG_JOURNAL_PATH": "your-value",
"KORG_LEDGER_HMAC_KEY": "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.
KORG_JOURNAL_PATH envKORG_LEDGER_HMAC_KEY 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 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto New1Direction 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 (0.6.3) kam vor 5 Monaten 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: 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 · 繁體中文
An AI coding teammate for your terminal — that keeps the receipts.
Tell korgex what you want in plain English — *"fix the failing test," "add a healthcheck endpoint"* — and it reads your code, makes the change, runs the tests, and shows you exactly what it did. It's free and open-source, and it works with whatever AI you prefer (Claude, ChatGPT, Gemini, Grok, or a private model running on your own computer), so you're never locked to one company.
Why it's different: everything korgex does is saved to a tamper-proof record you can check later. If anyone alters that record — even by a single character — korgex can prove it. It's a coding assistant you can *audit*, not just hope to trust.
For developers: terminal-native, plan-first, speaks both the Anthropic and OpenAI tool-use protocols, runs on any OpenAI- or Anthropic-compatible model (incl. local via Ollama), connects to any MCP server, streams live, and records every run to a hash-chained causal ledger you can check with korgex verify . MIT-licensed.
$ korgex "add a /healthz endpoint that returns 200 with uptime"
➤ Read(file_path=/app/routes.py) ➤ Edit(file_path=/app/routes.py, old_string=..., new_string=...) ➤ Bash(command=pytest tests/test_routes.py -q) ✓ Added GET /healthz returning {"status": "ok", "uptime_seconds": ...}
$ korgex verify ✓ ledger intact — 7 events, hash-chain + causal DAG verified
pip install -U korgex # or, for an isolated global CLI:
uv tool install korgex@latest
Requires Python ≥ 3.10 (tested on 3.10, 3.11, 3.12, 3.13).
maingit clone https://github.com/New1Direction/korgex.git && cd korgex && pip install -e .
pip install git+https://github.com/New1Direction/korgex.git
# 1. Connect a provider (interactive — saves to ~/.korgex/config.json)
korgex setup
export ANTHROPIC_API_KEY="sk-ant-..." export OPENAI_API_KEY="sk-proj-..." export KORGEX_API_KEY="sk-or-v1-..." KORGEX_API_URL="https://openrouter.ai/api/v1" # OpenRouter export KORGEX_API_URL="http://your-gpu-box:8000/v1" # self-hosted vLLM/llama.cpp → korgex --model Qwen2.5-Coder-32B "…"
korgex "fix the failing test in tests/test_auth.py"
korgex --model claude-sonnet-4-6 "refactor src/handler.py" korgex --mode plan "design a rate limiter for the API" korgex --quiet "list the python files in src/" # no TUI — pipe-friendly
korgex verify
Run bare korgex with no prompt to drop into the interactive REPL.
Run bare korgex for a streaming, multi-turn session. It connects your MCP servers, reads your project rules, and keeps a per-session rewind log.
Slash commands
| Command | What it does | |
|---|---|---|
/loop | Grind a task list unattended — auto-continues turn after turn until done, with a hard cap (Ctrl-C stops). | |
/diff [n] | Colored diffs of what changed in the last turn (or turn n). | |
/rewind [n] | List undo points, or restore files to BEFORE prompt n. | |
/skills · /skills curate | List skills korgex learned (✦); curate merges near-duplicates. | |
/tasks · /jobs | The live task checklist; background shell jobs. | |
| `/plan [on\ | off]` | Plan mode — read-only until you approve the agent's plan. |
/model [id] | Show a priced model menu, or switch the live model mid-session. | |
/verify · /cost | Verify the session ledger; show estimated $ spend from recorded tokens. | |
/resume [id] | Reload a prior session's transcript into context and continue where you left off. | |
/ [args] | Run a custom command — a markdown prompt from .korgex/commands/ (or a built-in like /code-review, /build-fix, /checkpoint). | |
/clear · /help · /exit | Reset the conversation · help · quit. |
Inline shortcuts
refactor @src/auth.py to use @src/db.py.!git status, !pytest -q.Project rules. korgex init scaffolds an AGENTS.md; korgex auto-reads it — plus any nested AGENTS.md up the tree and .korgex/rules/*.md — every session, so it follows your house style.
Prompt caching keeps the system prompt + tools warm across turns (automatic on OpenAI/Gemini/Grok/DeepSeek; cache_control breakpoints on Claude/Qwen). Set KORGEX_CACHE_STATS=1 to see per-turn cache hits — and every hit is recorded on the ledger, so korgex cost prices cached tokens at their real discounted rate (and shows what the cache saved you), provable with korgex verify.
flowchart TD
U["You — prompt or REPL"] --> CLI["korgex CLI / REPL"] CLI --> AG["KorgexAgent loop plan → act → verify"] AG -->|model id| PB{Provider} PB -->|"claude / anthropic/*"| ANT["Anthropic SDK"] PB -->|everything else| OAI["OpenAI-compatible SDK OpenAI · OpenRouter · Ollama · Grok · DeepSeek"] ANT --> TR["Tool router (src/tool_abstraction.py)"] OAI --> TR TR --> BT["Built-in tools Read · Edit · Bash · Grep · …"] TR --> MCP["MCP servers (any in mcp.json)"] TR --> CA["CodeAct kernel code = the action (opt-in)"] BT --> LED[("korg-ledger hash-chained + causal DAG")] MCP --> LED CA --> LED LED -. "verify · trace · why · cost" .-> U
The agent is provider-agnostic by design: tool schemas are translated per provider ({name, description, input_schema} for Anthropic, {type:"function", function:{…}} for OpenAI), responses are normalized into a common shape, and tool results are formatted in whichever message structure the provider expects. Every tool call — built-in, MCP, or CodeAct — is recorded to the ledger as it happens.
In plain terms: korgex keeps a logbook of everything it does — every file it reads, every command it runs. Each entry is sealed to the one before it, like links in a chain, so if anyone later changes, adds, or removes even one entry, the chain visibly breaks. The result is honest, checkable proof of what the AI actually did — for audits, compliance, debugging, or simple peace of mind. As far as we know, no other coding agent does this.
Under the hood: every run is recorded to a tamper-evident causal ledger, not an opaque log. Each event is hash-linked (prev_hash/entry_hash) to the previous one *and* causally linked (triggered_by) to what caused it — so a whole session can be cryptographically proven intact, and any edit, deletion, reorder, or splice is detected and localized to the offending event.
flowchart LR
subgraph chain["korg-ledger — each event hash-linked to the last"] direction LR E0["prompt a1f3"] --> E1["Read 7c0e"] --> E2["Edit b42d"] --> E3["Bash: pytest 9d11"] end E3 --> V{{"korgex verify"}} V -->|chain intact| OK["✓ proven unaltered"] V -->|"edit / splice / reorder"| BAD["✗ localized to the bad event"]
korgex verify # prove the recorded run wasn't altered (exit 0/1, CI-friendly)
korgex trace # the causal trace — what the agent did + what caused it korgex why src/auth.py # walk the causal chain back from a file change to its prompt korgex recall "rate limiter" # pull lean, verified context for a query — retrieve, don't carry korgex cost # estimated $ spend for the session, from recorded token counts export KORG_LEDGER_HMAC_KEY=… # make the chain tamper-PROOF, not just tamper-evident
Memory drift. A remembered fact is anchored to a sha256 baseline of its source, so when the source moves on the staleness is an exact signal — and the keep/refresh/discard reconcile decision is itself recorded to the ledger.
korgex drift # scan persistent memories for drift vs their source baselines (exit 0/1)
Audit logs you already have — and share the proof. korgex audit imports a session you already ran (auto-discovers your Claude Code logs) into a verifiable chain. Add --html and you get a single self-contained file that re-verifies itself in the recipient's browser — including a live *tamper test* that breaks the chain on purpose so anyone can feel the evidence. No setup, no buy-in, no network calls.
korgex audit --html audit.html
korgex import transcript.json # replay any vendor's session into a korg-ledger@v1 journal korgex trajectory --out train.jsonl # export the journal as a provenance-stamped training trajectory
Hand someone a receipt. korgex receipt mints a single portable file that proves what a run did — the events (so it checks offline), a plain-language --claim, a summary, and an optional --sign that attests *who* with your own key. The recipient confirms it with korgex receipt verify (exit 0/1), or just opens the --html and watches it re-verify itself. A provable deliverable, not a screenshot.
korgex receipt --claim "shipped /healthz + passing test" --sign --html receipt.html
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