korgex 0.24.0

Autonomous AI coding agent — provider-agnostic, MCP-native, plan-first

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

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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

Command	What it does
/loop <task>	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.
/<name> [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

• @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.

---

How it works

flowchart TD
    U["You — prompt or REPL"] --> CLI["korgex CLI / REPL"]
    CLI --> AG["KorgexAgent loop<br/>plan → act → verify"]
    AG -->|model id| PB{Provider}
    PB -->|"claude / anthropic/*"| ANT["Anthropic SDK"]
    PB -->|everything else| OAI["OpenAI-compatible SDK<br/>OpenAI · OpenRouter · Ollama · Grok · DeepSeek"]
    ANT --> TR["Tool router<br/>(src/tool_abstraction.py)"]
    OAI --> TR
    TR --> BT["Built-in tools<br/>Read · Edit · Bash · Grep · …"]
    TR --> MCP["MCP servers<br/>(any in mcp.json)"]
    TR --> CA["CodeAct kernel<br/>code = the action (opt-in)"]
    BT --> LED[("korg-ledger<br/>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<br/>a1f3"] --> E1["Read<br/>7c0e"] --> E2["Edit<br/>b42d"] --> E3["Bash: pytest<br/>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 <session> → 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 <file> (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, 2 files, $0.0078
#   signed by b251a84c… (your korgex identity) · tip 46263017…
#   receipt.html  ← open in any browser; it re-verifies itself

korgex receipt verify receipt.korgreceipt.json   # ✓ VALID / ✗ INVALID (CI-gateable)

See Self-Coding Bench for live reliability data across models.

---

Tools

The agent sees 23 high-level, model-facing tools (Claude-Code style), each with a deep description covering usage, edge cases, and anti-patterns. Under the hood they route to ~60 internal handlers (src/tools_impl.py).

Tool	Purpose
Read · Write · Edit	Read a file; create/overwrite; surgical string-replace (converted to SEARCH/REPLACE internally).
Bash · BashOutput	Run a shell command with timeout; poll a long-running background job.
Grep · Glob	Regex content search (ripgrep where available); list files by pattern.
Agent · Orchestrate	Delegate a sub-task to a sub-agent; run a parallel DAG of sub-agents (see Capabilities).
TaskCreate · TaskUpdate	Track and update multi-step work as a task list.
AskUserQuestion	Ask a clarifying question with optional multiple-choice.
Skill · ToolSearch	Invoke an installed skill; discover tools at runtime by keyword.
WebFetch · WebSearch	Fetch a URL as clean text; search the web.
Recall	Pull relevant facts from cross-session memory (drift-checked).
Retrieve	Pull the exact bytes of a large tool result that was sealed to a content-ref.
BusSend · BusInbox	Send/receive on the verifiable agent message bus (tamper-evident coordination).
python (opt-in)	CodeAct — run Python as the action, with tools available as functions.
NetCapture (opt-in)	Auditable HTTP(S) capture of an app you wrote — debug API calls without cURL.
RemoteSignTip (opt-in)	Sign a ledger tip via a remote signer you control (key off-host).

---

Capabilities

Beyond the core file/shell/search loop, korgex ships several deeper systems. The riskier ones are opt-in and off by default (a single env var), and every one of them records to the verifiable ledger.

• CodeAct — code as the action space (KORGEX_CODEACT_ENABLE=1). A persistent, fuel-metered Python kernel where the model writes code that calls tools as functions — denser than one-tool-call-per-turn. The nested execution trace is recorded to the ledger; optional OS-level isolation via bubblewrap on Linux (KORGEX_CODEACT_ISOLATION=1).
• Multi-agent orchestration (KORGEX_PARALLEL_AGENTS, plus the Orchestrate tool). Run a DAG of sub-agents concurrently — ledger-native and verifiable, with hard one-level nesting and each sub-run chained under its parent.
• Auditable network capture (KORGEX_NETCAPTURE_ENABLE=1). Run an app/script you wrote under a local CA-signing capture proxy and get a structured, redacted trace of every HTTP(S) exchange. Process-scoped, capture-only, secrets masked before they're recorded.
• Verifiable browser (KORGEX_BROWSER_STEALTH, KORGEX_BROWSER_EVAL). CDP-driven snapshot→act browser automation, ledger-recorded; opt-in stealth.
• Remote signing (KORGEX_REMOTE_SIGNER_*). Sign a ledger tip via an HTTP signer you own and control, so the signing key can live off the agent host (a separate box, an HSM). Fail-closed: bearer token, host allowlist, optional pubkey pinning, local signature verification.
• Verifiable agent bus (korgex bus, KORG_BUS_*). Agents coordinate over an Ed25519-signed, tamper-evident korg-ledger journal — "who said what" is a signature, not a claim.
• Recall + memory — cross-session memory that is drift-checked against source baselines (Verifiable cognition).
• Local models (korgex local). Hardware-aware advisor (CPU/RAM/GPU/VRAM → ranked, fit-scored picks via llmfit, optional) that can wire a local Ollama model as your default.

---

Safety & sandboxing

• Destructive-command guard (on by default; KORGEX_COMMAND_GUARD). A whitelist-first, quote/comment-aware floor over Bash (and the CodeAct bridge) that refuses obviously destructive commands; a block is a tamper-evident command_guard.block event in the ledger.
• Bash sandbox (KORGEX_SANDBOX=modal|docker|direct|auto). Controls isolation for shell execution.
• CodeAct OS isolation (KORGEX_CODEACT_ISOLATION=1, Linux/bubblewrap) for the code kernel.
• Edit confirmation. Diffs for Edit/Write on critical files prompt [y/N] in the TUI; the edit policy is configurable via KORGEX_EDIT_POLICY.
• Opt-in by default for anything powerful. CodeAct, NetCapture, remote signing, and browser stealth are all off until you turn them on.

---

CLI reference

$ korgex --help
usage: korgex [-h] SUBCOMMAND ...

korgex — autonomous coding agent. Pass a naked prompt to run the agent, or use a subcommand.

Any non-subcommand argument is treated as a prompt: korgex "create hello.txt with 'hi'".

Flags

Flag	Purpose
--model MODEL	Override the model (e.g. claude-sonnet-4-6, gpt-4o, openai/gpt-4o-mini). Always wins over --mode.
--mode {plan,execute,explore,review,debug,research}	Mode-based model selection (see Multi-model routing).
--mcp	Load MCP servers from mcp.json at startup.
--quiet / -q	Disable the streaming TUI; only the final result prints. Use in pipes, scripts, CI.
--version / -V	Print the korgex version and exit.
--resume	Resume the last session — replay its transcript from the verifiable ledger. With a prompt: resume + run it; bare korgex --resume: reopen the REPL with that context.

Subcommands

Subcommand	Behavior
korgex setup	Connect model providers (any of them) — saves keys + a default model to ~/.korgex/config.json.
korgex init	Scaffold a starter AGENTS.md for the repo (detects stack + test/build commands; never clobbers).
korgex skills	List every available skill (built-in, project, learned) with its description.
korgex sessions	List recent sessions in this repo's ledger (resume one with korgex --resume).
korgex commands	List custom slash commands (built-in, project, user); invoke them in the REPL as /<name>.
korgex local	Recommend (and optionally wire) a local model that fits this machine.
Verifiable cognition
korgex verify [journal]	Prove the ledger's hash-chain + causal DAG is intact (exit 0/1, CI-friendly).
korgex trace	Show the causal cognition trace — what the agent did and what caused it.
korgex why <path>	Trace why a file was changed, back through the causal chain to its prompt.
korgex cost	Estimated $ spend for the session, from the ledger's recorded token counts.
korgex drift	Scan persistent memories for drift against their source baselines (exit 0/1).
korgex audit [--html f]	Audit a session you already ran into a verifiable ledger (auto-discovers Claude Code logs).
korgex import <file>	Replay another vendor's session transcript into a korg-ledger@v1 journal.
korgex trajectory	Export a journal as a verifiable, provenance-stamped training trajectory.
korgex bus	Verifiable agent message bus over a tamper-evident korg-ledger journal.
MCP & integrations
korgex mcp	Manage MCP servers — add/list/remove stdio or remote (url+auth) servers in mcp.json.
korgex mcp-server	Run the korg-ledger MCP server (JSON-RPC over stdio) — verify/audit/import for any MCP host.
korgex diag <path>	Report language-server diagnostics (errors/types) for a file — best-effort.
Dashboard / editor
korgex serve · dashboard	Start the FastAPI dashboard (:8090) with/without opening the VS Code sidecar.
korgex status · stop	Report / terminate the background backend.
korgex install-extension	Install the compiled .vsix into your local VS Code.

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Environment variables

Core

Variable	Purpose	Default
ANTHROPIC_API_KEY	Used when the model id contains "claude" or starts with "anthropic/".	—
OPENAI_API_KEY	Used for any non-Anthropic model.	—
KORGEX_API_KEY / KORGEX_API_URL	Generic key + base URL for OpenAI-compatible endpoints (OpenRouter, Ollama, vLLM…).	— / https://api.openai.com/v1
KORGEX_MODEL	Default model when neither --model nor --mode is given.	claude-sonnet-4-6
KORGEX_PROVIDER	Force the transport (openai|anthropic), overriding model-id autodetect.	autodetect
KORGEX_MAX_ITERATIONS	Max agent-loop iterations before giving up.	30
KORGEX_MCP	1 to auto-load MCP servers from mcp.json.	unset
KORGEX_SANDBOX	modal|docker|direct|auto — bash isolation.	auto

Capabilities (opt-in)

Variable	Purpose
KORGEX_LEAN_CONTEXT · KORGEX_LEAN_CONTEXT_TOKENS	Inject lean, verified ledger context relevant to the prompt instead of carrying full history (budget default 800) — lets a smaller/self-hosted model run the loop.
KORGEX_CODEACT_ENABLE · KORGEX_CODEACT_ISOLATION	Enable the CodeAct code-kernel; OS isolation (Linux/bubblewrap).
KORGEX_NETCAPTURE_ENABLE	Enable the auditable HTTP(S) capture tool.
KORGEX_PARALLEL_AGENTS	Concurrency for multi-agent orchestration.
KORGEX_REMOTE_SIGNER_TOKEN · _ALLOWED_HOSTS · _PUBKEY · _REQUIRE_HTTPS	Remote-signer auth, host allowlist, pinned key, https enforcement.
KORGEX_BROWSER_STEALTH · KORGEX_BROWSER_EVAL	Browser stealth mode; allow in-page evaluate.
KORGEX_COMMAND_GUARD	Toggle the destructive-command guard (on by default).
KORGEX_EDIT_POLICY	Edit confirmation policy.

Ledger & bus

Variable	Purpose	Default
KORG_JOURNAL_PATH	Durable JSONL ledger; content-addressed blobs are written beside it.	.korg/journal.jsonl
KORG_LEDGER_HMAC_KEY	If set, the chain is HMAC-keyed — tamper-proof, not just tamper-evident.	unset
KORG_BUS_AGENT · KORG_BUS_JOURNAL · KORG_BUS_KEY	Agent id, bus journal, and Ed25519 key for the verifiable bus.	—

Provider-detection rule: if the model id contains "claude" or starts with "anthropic/", the Anthropic SDK is used; otherwise the OpenAI-compatible SDK (OpenAI, OpenRouter, Ollama, DeepSeek, vLLM, …). Set KORGEX_PROVIDER=openai to drive a claude/anthropic/* id through an OpenAI-compatible endpoint (e.g. Claude via OpenRouter).

---

Multi-model routing

--mode picks a model appropriate for the work type:

Mode	Model	Generation params
plan	Opus 4.7	max_tokens=64000, thinking={budget_tokens: 20000}, temperature=0.7
execute	Sonnet 4.6	max_tokens=64000, temperature=0.3
explore	Opus 4.7	max_tokens=32000, temperature=0.5
review	Sonnet 4.6	max_tokens=16000, temperature=0.3
debug	Haiku 4.5	max_tokens=16000, temperature=0.2
research	Opus 4.7	max_tokens=32000, temperature=0.7

Explicit --model always wins over --mode. Default (neither set) is Sonnet 4.6.

korgex --mode plan "architect a multi-tenant billing system"
korgex --mode debug "trace why this 500 is happening"
korgex --mode execute "implement the plan we just made"

---

MCP integration

Plain version: MCP is an open "app-store" standard for AI — it lets korgex plug into outside services (GitHub, your files, a database, …) without custom glue.

korgex includes a native MCP (Model Context Protocol) client. Any MCP server in your mcp.json becomes part of the agent's tool surface. Manage them from the CLI with korgex mcp (add/list/remove stdio or remote url+auth servers).

korgex is an MCP server too

korgex mcp-server exposes the verifiable-cognition substrate over JSON-RPC/stdio so any MCP host (Claude Desktop, Cursor, …) can call:

• korg_verify — prove a korg-ledger journal is tamper-evident-intact;
• korg_audit — audit the host agent's own Claude Code logs (import + verify), zero-config;
• korg_import — import a vendor session transcript into a verifiable chained ledger.

{ "mcpServers": { "korg-ledger": { "command": "korgex", "args": ["mcp-server"] } } }

Listed in the MCP Registry — mcp-name: io.github.New1Direction/korg-ledger.

Configure & use

{
  "mcpServers": {
    "github":     { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-github"],     "env": { "GITHUB_TOKEN": "ghp_..." } },
    "filesystem": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"] }
  }
}

korgex --mcp "create a GitHub issue summarizing today's bug"

The agent discovers each server's tools at startup, registers them into the user-facing tool list, and routes calls back to the originating server. Server failures are logged and skipped — they never crash the agent.

---

Plugins

Extend korgex without forking it. Drop a .py file into ~/.korgex/plugins/ (global) or <repo>/.korgex/plugins/ (project-local) that defines a register(registry) function, and it hooks into the agent loop at startup.

# ~/.korgex/plugins/notify.py — ping me when a file is edited
def register(reg):
    @reg.on("post_tool")
    def on_edit(payload):
        call = payload["call"]
        if call["name"] in ("Edit", "Write"):
            print(f"  ✎ touched {call['args'].get('file_path')}")

Lifecycle hooks: on_user_prompt (each turn starts), pre_tool (before a tool runs), post_tool (after it returns), on_stop (run finishes). Plugins run in-process with full access — install only ones you trust — and are fail-safe: one that fails to import, lacks register, or raises is recorded and skipped without crashing startup.

---

Streaming TUI

When stdout is a TTY, the agent streams output live via Rich: thinking blocks in dimmed italic (Anthropic), text character-by-character, tool calls with a transient spinner (⠋ Read(file_path=src/foo.py)), [y/N] diff confirmation on critical edits, and graceful Ctrl+C interrupt (double to force-kill). Streaming auto-disables when stdout is piped, in CI, or with --quiet. OpenAI/OpenRouter streaming pipes through the same renderer; tool-call deltas are accumulated across chunks.

---

Architecture

Tool routing — stable model-facing names → internal handlers

User tool call (LLM-visible):     Internal handler (src/tools_impl.py):
─────────────────────────────     ─────────────────────────────────────
Read(file_path=...)         →     tool_read_file(filepath=..., context=...)
Write(file_path=..., ...)   →     tool_write_file(filepath=..., ...)
Edit(file_path, old, new)   →     tool_replace_with_git_merge_diff(merge_diff="<<<<<<< SEARCH ...")
Bash(command=...)           →     tool_run_in_bash_session(command=...)

The router (src/tool_abstraction.py) looks up the name in _TOOL_ROUTING, applies a param_map or a custom adapter, filters kwargs the handler doesn't accept, auto-injects context={'repo_root': cwd}, and catches exceptions into {"error": ...} so a single tool failure never kills the loop. MCP-sourced tools bypass _TOOL_ROUTING and dispatch through MCPServerManager.call_tool().

The agent loop

flowchart TD
    S(["prompt"]) --> SEND["LLM.send(messages, tools)"]
    SEND --> Q{tool calls?}
    Q -->|no| F(["final result"])
    Q -->|yes| RT["route_tool_call(name, args)"]
    RT --> REC["record event → korg-ledger"]
    REC --> APP["append tool_result to messages"]
    APP --> SEND

The plan-first system prompt directs the agent to plan, verify, diagnose-before-changing, and never modify build artifacts (SYSTEM_PROMPT in src/agent.py). The ledger lives in native Python (src/korg_ledger.py, src/ledger_spec.py) — no external runtime required.

---

Project structure

korgex/
├── src/
│   ├── agent.py              # KorgexAgent — main loop, provider branching, streaming
│   ├── cli.py · repl.py      # argparse dispatch · interactive REPL
│   ├── tool_abstraction.py   # USER_TOOLS registry + router + MCP integration
│   ├── tools_impl.py         # ~60 internal handlers (file ops, git, GitHub, web, …)
│   ├── model_router.py       # mode → model mapping (plan/execute/debug/…)
│   ├── korg_ledger.py · ledger_spec.py · signing.py   # verifiable ledger + Ed25519
│   ├── codeact/              # code-as-action kernel (fuel-metered, isolated, traced)
│   ├── orchestrate.py        # multi-agent DAG orchestration
│   ├── recall.py · memory.py · memory_drift.py        # cross-session memory + drift
│   ├── command_guard.py · sandbox.py                  # destructive-cmd floor · bash sandbox
│   ├── netcapture.py · remote_signer.py · browser.py  # opt-in capability modules
│   ├── structured_output.py · skills.py · local_model.py
│   ├── mcp_client.py · dashboard.py · interactive.py
│   └── ...
├── docs/                     # CLI reference, comparison, getting-started, tools-reference, …
├── spec/korg-ledger-v1/      # the ledger spec (SPEC.md, EVENTS.md)
├── tests/                    # ~1,263 tests
├── .github/workflows/        # Linux CI (3.10–3.13) + PyPI publisher (OIDC)
├── pyproject.toml
└── README.md

---

Development & testing

git clone https://github.com/New1Direction/korgex.git && cd korgex
uv venv .venv && source .venv/bin/activate      # or python -m venv .venv
uv pip install -e ".[dev]"                       # pytest, build, ruff, …

ruff check src/                                   # lint
pytest -q                                         # the full suite

The suite is ~1,285 tests with no live LLM calls (everything is unit-tested) and runs on Linux CI across Python 3.10, 3.11, 3.12, 3.13 on every push and PR. Major areas: the agent loop (routing, provider schemas, mode/model resolution, loop guards, the stall classifier, compaction), tools (fuzzy Edit, edit-freshness, background Bash, web), the verifiable ledger (hash-chain + causal DAG, redaction, the Ed25519 signed bus), CodeAct (kernel isolation, fuel, the tool bridge), MCP (namespaced multi-server router, OAuth refresh, full round-trip), prompt caching, skills (trust tiers, self-learning, the curator), and the REPL.

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Building & releasing

Releases are automated. Bump version in pyproject.toml, update CHANGELOG.md, merge to main, then cut a GitHub Release — the PyPI publish workflow fires on release: published and uploads via OIDC Trusted Publishing (with digital attestations). No manual token handling.

gh release create vX.Y.Z --title "vX.Y.Z" --notes "…"   # → triggers .github/workflows/publish.yml → PyPI

To build locally for inspection: python -m build then python -m twine check dist/*.

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Troubleshooting

korgex: No API key found — set one of ANTHROPIC_API_KEY, OPENAI_API_KEY, or KORGEX_API_KEY (with KORGEX_API_URL for non-OpenAI endpoints), or run korgex setup.

ModuleNotFoundError: No module named 'anthropic' (or openai, rich) — the deps weren't installed: pip install -e . (picks up everything from pyproject.toml).

Agent loops forever on tool calls — lower the cap: export KORGEX_MAX_ITERATIONS=10, and use --quiet to see only the final state.

--mcp is slow to start — the client connects to each server synchronously and waits for the handshake; unreachable entries in mcp.json each time out before being skipped. Remove dead servers or use korgex mcp to manage them.

verify reports a break — that's the point: it found and localized an altered/spliced event. The reported seq_id is where the chain diverges.

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Known limitations

These exist today; PRs welcome.

• OpenAI streaming has fewer rendered events than Anthropic. Anthropic emits thinking blocks and message-delta usage; OpenAI emits only text and tool-call chunks. Both render correctly, but the TUI is richer for Anthropic.- Dashboard authentication is not implemented. Don't expose port 8090 publicly without an auth-terminating reverse proxy in front.
• The VS Code sidecar is a legacy companion to the dashboard; korgex's primary interface is the terminal REPL.

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License

MIT — see LICENSE.

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Related projects

• Model Context Protocol — the open MCP standard korgex implements (as both client and server).
• korg · korgchat — the broader ecosystem around the korg-ledger.
• llmfit — the hardware-aware local-model advisor korgex local builds on (optional).