原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Korg Ledger

作者:New1Direction版本 0.6.3i★ –i在你的电脑上运行
注册名称io.github.New1Direction/korg-ledger

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 会计、财务与税务

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: KORG_JOURNAL_PATH, KORG_LEDGER_HMAC_KEY

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

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

在终端中运行这条命令

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

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • 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.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 New1Direction 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“会计、财务与税务”中的其他服务器比较i

  • 星标数多于此分类中其他 1734 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1734 个服务器的 10% 更新
  • 基础检查结果等于或优于此分类中其他 1734 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Korg Ledger 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.6.3)于5个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Finance Toolkit, SolidInvoice, Korea Tax Calculator

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Finance Toolkit

作者:JerBouma

500+ transparent financial methods calculated from raw statements, not third-party endpoints.

电脑或云端★ 5,496MIT今天更新
安装

SolidInvoice

作者:SolidInvoice

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

在云端运行★ 981MIT8天前更新
安装

Korea Tax Calculator

作者:UpstageAI

Korean tax calculation and tax-audit judgment MCP: 96 tools with statutory citations.

在你的电脑上运行★ 97MIT昨天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx