nucleus-brain — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited nucleus-brain (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.eidetic-works/nucleus -->
.brain — the portable decision logThe portable decision log your AI tools all read. One MCP server. Any AI tool. Plain files.
Every AI coding session starts by re-explaining context the last session already knew. .brain is a folder in your repo that Claude Code, Cursor, and Codex all read via one MCP server. Decisions, policies, plans — written once, remembered across every session and every tool.
MIT licensed. File-based (plain JSON + markdown). No embeddings. No vendor lock-in.
nucleus-mcp ships a second, fully independent tool: nucleus-rabbithole, a rabbit-hole depth tracker for focus-prone developers.
It gives your AI a push/pop depth stack, a context-switch thrash detector, an open-loop externaliser, and a weekly review — all backed by local SQLite, no network, no daemon.
# Already installed with nucleus-mcp — just run:
nucleus-rabbitholeClaude Code .mcp.json snippet:
{
"mcpServers": {
"nucleus-rabbithole": {
"command": "nucleus-rabbithole",
"args": []
}
}
}Full documentation: docs/RABBITHOLE.md
The core loop that makes AI reliability compound over time:
GROUND ALIGN COMPOUND
────── ───── ────────
Machine verifies Human corrects System learns
AI writes code → You fix a mistake → Delta recorded
GROUND checks → Verdict stored → DPO pair created
Receipt logged → Event emitted → Training data grows
│ │ │
└───────────────────┴────────────────────┘
Reliability improvesGROUND — 5-tier execution verification. Syntax, imports, tests, runtime. Goes outside the formal system to check the AI's work.
ALIGN — One-call corrections. nucleus_align(action="correct", params={context, correction}). Each correction automatically records a verdict, creates a training pair, and emits an event.
COMPOUND — Deltas measure the gap between intent and reality. Recurring patterns become strategy. Negative deltas become training signal.
Every tool response shows frontier health:
[frontiers: GROUND 42 | ALIGN 12 | COMPOUND 28]Option A — No install (ChatGPT, Claude, Perplexity):
Add https://relay.nucleusos.dev/mcp as a remote MCP server in your platform's connector settings. That's it — your AI now has persistent memory.
Option B — Local install (Cursor, Windsurf, Claude Desktop):
pip install nucleus-mcp
nucleus init --recipe founderTwo commands. Nucleus is running. AI outputs are now verified. nucleus init auto-configures your MCP client — just restart it.
114 MCP tools across 13 facades:
Benchmark: decision-retention-evals — does your AI agent remember why the code is the way it is?
Everything above is free (MIT). Nucleus Pro adds verifiable governance:
nucleus trial # 14-day free trial
nucleus compliance-check # Score your AI governance
nucleus audit-report --signed -o report.html # Cryptographically signed report$19/month or $149/year — nucleusos.dev/pricing
| Free | Pro | |
|---|---|---|
| 13 tools, 10 resources, 3 prompts | Yes | Yes |
| Persistent memory | Yes | Yes |
| Governance & HITL | Yes | Yes |
| Audit trails (DSoR) | Yes | Yes |
| Signed audit reports | - | Ed25519 |
| Compliance exports | Score only | Full PDF/HTML |
| Priority issues | - | Yes |
| IDE | Install |
|---|---|
| Cursor | Add to Cursor |
| Claude Code | npx -y nucleus-mcp |
| Any IDE | pip install nucleus-mcp |
pip install nucleus-mcpOr use npx (zero Python setup required):
npx -y nucleus-mcpAdd to your MCP config (claude_desktop_config.json or equivalent):
{
"mcpServers": {
"nucleus": {
"command": "npx",
"args": ["-y", "nucleus-mcp"]
}
}
}<details> <summary>Alternative: use pip install directly</summary>
{
"mcpServers": {
"nucleus": {
"command": "python3",
"args": ["-m", "mcp_server_nucleus"],
"env": {
"NUCLEUS_BRAIN_PATH": "/path/to/your/project/.brain"
}
}
}
}</details>
Add to .mcp.json in your project root:
{
"mcpServers": {
"nucleus": {
"command": "npx",
"args": ["-y", "nucleus-mcp"]
}
}
}Nucleus finds your .brain automatically:
NUCLEUS_BRAIN_PATH environment variable (explicit).brain/ directory$HOME/.nucleus/brainNucleus has a full CLI alongside the MCP tools. Auto-detects TTY (table output) vs pipe (JSON).
# Memory
nucleus engram write my_key "insight here" --context Decision --intensity 7
nucleus engram search "compliance"
nucleus engram query --context Strategy --limit 10
# Tasks
nucleus task list --status READY
nucleus task add "Ship the feature" --priority 1
# Sessions
nucleus session save "Working on auth refactor"
nucleus session resume
# Health
nucleus status --health
nucleus sovereign
# Compliance
nucleus comply --jurisdiction eu-dora
nucleus audit-report --format html -o report.html
# Chat (multi-provider: Gemini, Anthropic, Groq)
nucleus chatPipe-friendly:
nucleus engram search "test" | jq '.key'
nucleus task list --format tsv | cut -f1,3One-command configuration for regulatory frameworks:
nucleus comply --jurisdiction eu-dora # EU DORA
nucleus comply --jurisdiction sg-mas-trm # Singapore MAS TRM
nucleus comply --jurisdiction us-soc2 # US SOC2| Jurisdiction | Retention | HITL Ops | Kill Switch |
|---|---|---|---|
eu-dora | 7 years | 5 types | Required |
sg-mas-trm | 5 years | 5 types | Required |
us-soc2 | 1 year | 3 types | Optional |
global-default | 90 days | 2 types | Optional |
Nucleus collects anonymous, aggregate usage statistics (command name, duration, error type, versions, OS). No engram content, no file paths, no prompts, no API keys, no PII — ever.
nucleus config --no-telemetry
# or: NUCLEUS_ANON_TELEMETRY=falseSee TELEMETRY.md for details.
MIT © 2026 | [email protected]
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.