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Korg Ledger

by New1Directionversion 0.6.3i★ –iRuns on your computer
Registry nameio.github.New1Direction/korg-ledger

Install

Overview

Description from the maker (original English)

Verifiable cognition: prove a session ledger is tamper-evident; audit & import any agent's logs.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Accounting, finance & tax

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: KORG_JOURNAL_PATH, KORG_LEDGER_HMAC_KEY

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "korg-ledger": {
      "command": "uvx",
      "args": [
        "korgex"
      ],
      "env": {
        "KORG_JOURNAL_PATH": "your-value",
        "KORG_LEDGER_HMAC_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add korg-ledger --env KORG_JOURNAL_PATH=your-value --env KORG_LEDGER_HMAC_KEY=your-value -- uvx korgex

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "korg-ledger": {
      "command": "uvx",
      "args": [
        "korgex"
      ],
      "env": {
        "KORG_JOURNAL_PATH": "your-value",
        "KORG_LEDGER_HMAC_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "korg-ledger": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "korgex"
      ],
      "env": {
        "KORG_JOURNAL_PATH": "your-value",
        "KORG_LEDGER_HMAC_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • KORG_JOURNAL_PATH env
    Path to the JSONL ledger journal (defaults to .korg/journal.jsonl).
  • KORG_LEDGER_HMAC_KEY env
    Optional HMAC key — makes the chain tamper-PROOF, not just tamper-evident.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account New1Direction, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Accounting, finance & taxi

  • More stars than 0% of the other 1734 servers in this category
  • Published to the registry more recently than 10% of the other 1734 servers in this category
  • Basic checks equal to or better than 100% of the other 1734 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Korg Ledger safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.6.3) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Finance Toolkit, SolidInvoice, Korea Tax Calculator

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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SolidInvoice

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Create and send invoices and quotes, manage clients, and track payments in SolidInvoice.

Runs in the cloud★ 981MITUpdated 8 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

English · 简体中文 · 繁體中文

korgex

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


Table of Contents

  • Install
  • Quickstart
  • The REPL — live in it
  • How it works
  • Verifiable cognition
  • Tools
  • Capabilities
  • Safety & sandboxing
  • CLI reference
  • Environment variables
  • Multi-model routing
  • MCP integration
  • Plugins
  • Streaming TUI
  • Architecture
  • Project structure
  • Development & testing
  • Building & releasing
  • Troubleshooting
  • Known limitations
  • License

Install

From PyPI (recommended)
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).

From source / latest main
git clone https://github.com/New1Direction/korgex.git && cd korgex && pip install -e .

or, without cloning:

pip install git+https://github.com/New1Direction/korgex.git


Quickstart

# 1. Connect a provider (interactive — saves to ~/.korgex/config.json)

korgex setup

…or just export a key; any of these works:

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 "…"

2. Run the agent on a naked prompt

korgex "fix the failing test in tests/test_auth.py"

3. Or pick a model / mode

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

4. Prove the run wasn't altered afterward

korgex verify

Run bare korgex with no prompt to drop into the interactive REPL.


The REPL — live in it

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

CommandWhat 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 curateList skills korgex learned (✦); curate merges near-duplicates.
/tasks · /jobsThe 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 · /costVerify 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 · /exitReset the conversation · help · quit.

Inline shortcuts

  • `@path/to/file` — mention a file and its contents are pulled into the turn: refactor @src/auth.py to use @src/db.py.
  • `!command` — run a shell command right there: !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.


How it works

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.


Verifiable cognition

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

audited → 2,319 ledger events

chain: ✓ INTACT — tamper-evident, cryptographically verifiable

report: audit.html ← open in any browser; it re-verifies itself

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

✓ receipt minted — 5 events, 3 tool calls

Only the beginning is shown; read the rest in the repo

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