The Nervous System

LLM Behavioral Enforcement Framework

7 mechanically enforced rules that prevent the most common failure modes when LLMs have access to real infrastructure: context loss, silent failures, file damage, goal drift, and overreach.

Built by Arthur Palyan at Palyan Family AI System. 30 tools including configuration drift detection, emergency kill switch, usage monitoring, and bot compliance auditing. Battle-tested on a 13-agent AI family running 29 processes 24/7 on a $24/month VPS (upgraded to 7.8GB RAM). SAM.gov registered (CAGE 19R10). 26 partners across 10 countries. 99+ violations caught, 0 bypassed.

The Problem

When you give an LLM access to your file system, bash, and production infrastructure, it will eventually:

• Edit a file it shouldn't touch
• Lose context between sessions and start over
• Drift from the original objective during long tasks
• Fail silently when a session times out
• Make logic changes without asking
• Disappear into debug loops

The Nervous System solves all of these with rules enforced by external mechanisms the LLM cannot override.

Install

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "nervous-system": {
      "command": "npx",
      "args": ["-y", "mcp-nervous-system"]
    }
  }
}

Claude Code

claude mcp add nervous-system npx mcp-nervous-system

Direct

npx mcp-nervous-system

Server starts on port 3475 with SSE, HTTP, and health endpoints.

Hosted (No Install)

The server is live and ready to use:

URL: https://api.100levelup.com/mcp-ns/
Protocol: MCP 2024-11-05 (Streamable HTTP + SSE)
Authentication: None required

NEW in v1.9.3

Platform Integration Guides - Working examples for governing multi-agent systems on the 3 biggest platforms plus any MCP client. Each guide gets you to governed agents in under 10 minutes.

• Ruflo (claude-flow) - Queen-Worker hive mind governance with preflight checks, drift audits, and violation logging to swarm_state
• Hivemind - Team chat agent governance with tool interception, heartbeat drift audits, and session handoffs
• Anthropic Agent Teams - Parallel agent governance via CLAUDE.md propagation with shared untouchable lists and unified audit trails
• Generic MCP - 5-minute setup for any MCP client (Claude Desktop, Claude Code, Cursor, Windsurf, Cline)

v1.9.3

Tamara Reference Implementation + Case Study (2 new resources) Production reference implementation of an autonomous AI operations manager built on the Nervous System. Includes full architecture documentation, build-your-own guide, and case study with real metrics from managing 13 agents across 5 platforms.

v1.9.3

drift_audit (free tier) Configuration drift detection across 5 scopes: roles, versions, files, processes, and website. Scans source-of-truth files (family-roles.json, package.json, UNTOUCHABLE_FILES.txt) against all downstream references - HTML pages, JSON configs, markdown docs, and running PM2 processes. Change one file, drift_audit tells you everywhere else that needs updating. The closed loop that keeps your entire system consistent.

Positioning: Auto mode decides what Claude CAN do. The Nervous System governs HOW it behaves while doing it.

The 7 Rules

| # | Rule | What It Prevents | |---|------|-----------------| | 1 | Dispatch Don't Do | Debug loops, rabbit holes. Tasks > 2 messages get dispatched. | | 2 | Untouchable | File damage. Protected files mechanically blocked from editing. | | 3 | Write Progress | Silent failures. Progress noted before each action. | | 4 | Step Back Every 4 | Goal drift. Forced reflection every 4 messages. | | 5 | Delegate and Return | Invisible work. Background tasks reported immediately. | | 6 | Ask Before Touching | Unauthorized changes. Logic changes need human approval. | | 7 | Hand Off | Context loss. Written handoffs every 3-4 exchanges. |

MCP Tools (21)

| Tool | Description | |------|------------| | get_framework | Complete framework: all rules, permission protocol, enforcement patterns | | guardrail_rules | The 7 core rules with triggers, enforcement, and failure modes | | preflight_check | File protection system: shell script blocks edits to protected files | | session_handoff | Context preservation: templates for handoff documents | | worklog | Progress documentation pattern | | violation_logging | Audit trail: timestamp, type, context for every violation | | step_back_check | Forced reflection system | | get_nervous_system_info | System overview and operational stats | | emergency_kill_switch | Emergency shutdown of all PM2 processes. Requires kill switch secret. Logs to tamper-evident audit trail | | verify_audit_chain | Walks the SHA-256 hash-chained audit log and verifies every entry. Returns chain integrity status | | dispatch_to_llm | Spawns a background LLM agent to handle a task. Checks RAM, enforces max 2 concurrent dispatches | | drift_audit | Configuration drift detection across roles, versions, files, processes, and website. Finds stale values everywhere. |

Kill Switch

The emergency_kill_switch tool provides an emergency shutdown capability. Send a POST request to /kill with the kill switch secret to immediately stop all PM2 processes. Every activation is logged to the tamper-evident audit trail with SHA-256 hash chaining, so kill switch events cannot be hidden or altered after the fact.

• Requires authentication (kill switch secret)
• Logs to hash-chained audit trail
• Returns confirmation with affected process count

Tamper-Evident Audit Trail

Every guardrail violation, kill switch activation, and dispatch event is recorded in a SHA-256 hash-chained audit log. Each entry includes the hash of the previous entry, making it cryptographically impossible to alter or delete past records without breaking the chain.

• Use verify_audit_chain to walk the entire chain and verify integrity
• Returns: valid/invalid status, entry count, and break point if tampered
• 99+ violations caught, 0 bypassed, 0 chain breaks

Dispatch to LLM

The dispatch_to_llm tool enables a brain + agents architecture. Instead of one LLM session doing everything, complex tasks get dispatched to background agents that run independently under the same 7 rules.

• Checks available RAM (requires 500MB+)
• Enforces max 2 concurrent dispatches
• Returns PID and log file path for monitoring
• Every dispatched agent runs under the same nervous system guardrails

EU AI Act Compliance

The Nervous System provides practical compliance tools for the EU AI Act. See the full compliance page at:

https://api.100levelup.com/family/eu-ai-act.html

Production Reference: Tamara

Tamara is an autonomous AI operations manager built on the Nervous System framework. She manages 13 AI agents across 5 platforms, serving 175+ countries accessible from a $12/month VPS - without dedicated DevOps staff.

Tamara is the proof that the Nervous System works in production. She runs 60-minute autonomous check cycles, detects configuration drift, dispatches remediation agents, and reports to the human operator only when judgment is needed.

• Case Study: Use the nervous-system://case-study resource for full production metrics
• Reference Implementation: Use the nervous-system://tamara-reference resource for architecture details and build-your-own guide
• Enterprise Support: For organizations deploying AI agent fleets at scale, implementation consulting is available at wa.me/18184399770
• Blog: Meet Tamara | Why AI Agent Management Is the Next Infrastructure Layer

Resources (7)

• nervous-system://framework - The complete framework
• nervous-system://quick-start - Quick start guide
• nervous-system://rules - The 7 core rules
• nervous-system://templates - Templates for handoffs, worklogs, preflight
• nervous-system://drift-audit - Configuration drift detection
• nervous-system://tamara-reference - Tamara autonomous ops manager reference implementation
• nervous-system://case-study - Palyan Family AI System production case study

Production Stats

From the live Palyan Family AI System deployment (Feb 28 - Mar 5, 2026):

• 58+ violations caught
• 29 edits blocked by preflight
• 100 files protected
• 0 rules bypassed
• 27 processes monitored
• 5 days continuous operation

Live Demo

Try it yourself (no login required):

• Interactive Demo - Talk to a governed LLM and try to break the rules
• Audit Dashboard - See real violation history with timeline
• System Status - Live health checks
• API Documentation - Full tool and resource reference
• Case Study - Production deployment data
• Plain English Rules - For non-technical stakeholders
• Incident Response - Detection, containment, resolution
• EU AI Act Compliance - Practical EU AI Act compliance tools

Integrations

Works with the major multi-agent platforms and any MCP client:

| Platform | Integration | Setup Time | |----------|------------|------------| | Ruflo (claude-flow) | Plugin hooks into Queen-Worker pipeline | 10 min | | Hivemind | MCP connector with tool interception | 10 min | | Anthropic Agent Teams | CLAUDE.md governance propagation | 10 min | | Any MCP Client | 3 lines of config | 5 min |

Each integration includes working code, example configs, and a step-by-step README.

Agent Skills

The Nervous System is also available as an Agent Skill following the open Agent Skills standard. Install the governance skill to teach any AI agent (Claude, Codex, Cursor, Copilot, VS Code) how to enforce behavioral guardrails in multi-agent systems.

See skills/multi-agent-governance/SKILL.md for the full skill definition.

Philosophy

"LLMs can't reliably self-enforce promises. Guardrails work via preflight.sh, violation logs, and catching drift. Build enforcement systems, don't make promises."

If a guardrail can be violated by the thing it guards, it is not a guardrail. It is a suggestion.

Every rule in the Nervous System is enforced by an external mechanism: a shell script, a timer, a separate monitoring process. The LLM cannot override, circumvent, or ignore them.

License

MIT