Finance Toolkit
500+ transparent financial methods calculated from raw statements, not third-party endpoints.
제작자가 쓴 설명(영어 원문)
Verifiable cognition: prove a session ledger is tamper-evident; audit & import any agent's logs.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
KORG_JOURNAL_PATH, KORG_LEDGER_HMAC_KEY필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"korg-ledger": {
"command": "uvx",
"args": [
"korgex"
],
"env": {
"KORG_JOURNAL_PATH": "your-value",
"KORG_LEDGER_HMAC_KEY": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add korg-ledger --env KORG_JOURNAL_PATH=your-value --env KORG_LEDGER_HMAC_KEY=your-value -- uvx korgex실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"korg-ledger": {
"command": "uvx",
"args": [
"korgex"
],
"env": {
"KORG_JOURNAL_PATH": "your-value",
"KORG_LEDGER_HMAC_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"korg-ledger": {
"type": "stdio",
"command": "uvx",
"args": [
"korgex"
],
"env": {
"KORG_JOURNAL_PATH": "your-value",
"KORG_LEDGER_HMAC_KEY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
KORG_JOURNAL_PATH envKORG_LEDGER_HMAC_KEY env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 New1Direction 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.6.3)은 5개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Finance Toolkit, SolidInvoice, Korea Tax Calculator
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요