pip install agent-os-kernel

from agent_os import StatelessKernel, ExecutionContext

# Create a governed agent in 3 lines
kernel = StatelessKernel()

# Define execution context with governance policies
ctx = ExecutionContext(agent_id="demo-agent", policies=["read_only"])

# Your agent runs with policy enforcement
result = await kernel.execute(
    action="database_query",
    params={"query": "SELECT * FROM users"},
    context=ctx
)

# ✅ Safe queries execute
# ❌ "DROP TABLE users" → Blocked by kernel

git clone https://github.com/imran-siddique/agent-os && python agent-os/demo.py

from agent_os import StatelessKernel

kernel = StatelessKernel()
kernel.load_policy_yaml("""
version: "1.0"
name: api-safety
rules:
  - name: block-destructive-sql
    condition: "action == 'database_query'"
    action: deny
    pattern: "DROP|TRUNCATE|DELETE FROM .* WHERE 1=1"
  - name: rate-limit-api
    condition: "action == 'api_call'"
    limit: "100/hour"
""")

result = await kernel.execute(action="database_query", params={"query": "DROP TABLE users"})
# ❌ Blocked: Matched rule 'block-destructive-sql'

from agent_os import KernelSpace

kernel = KernelSpace()

# Every kernel action is automatically recorded
result = await kernel.execute(action="read_file", params={"path": "/data/report.csv"})

# Query the flight recorder
entries = kernel.flight_recorder.query(agent_id="agent-001", limit=10)
for entry in entries:
    print(f"{entry.timestamp} | {entry.action} | {entry.outcome}")

from agent_os import KernelSpace
from agent_os.emk import EpisodicMemory

kernel = KernelSpace(policy_file="policies.yaml")
memory = EpisodicMemory(max_turns=50)

@kernel.register
async def chat(message: str, conversation_id: str = "default") -> str:
    history = memory.get_history(conversation_id)
    response = await call_llm(history + [{"role": "user", "content": message}])
    memory.add_turn(conversation_id, message, response)
    return response
# Outputs are checked against content policies; violations trigger SIGSTOP

from agent_os import stateless_execute

# 1. Define safety policies (not prompts — actual enforcement)

# 2. Actions are checked against policies before execution
result = await stateless_execute(
    action="database_query",
    params={"query": "SELECT revenue FROM sales"},
    agent_id="analyst-001",
    policies=["read_only"]
)
# ✅ Safe queries execute
# ❌ "DROP TABLE users" → BLOCKED (not by prompt, by kernel)

from agent_os import KernelSpace, AgentSignal, AgentVFS

# Requires: pip install agent-os-kernel[full]
kernel = KernelSpace()
ctx = kernel.create_agent_context("agent-001")
await ctx.write("/mem/working/task.txt", "Hello World")

┌─────────────────────────────────────────────────────────┐
│              USER SPACE (Agent Code)                    │
│   Your agent code runs here. The kernel intercepts      │
│   actions before they execute.                          │
├─────────────────────────────────────────────────────────┤
│              KERNEL SPACE                               │
│   Policy Engine │ Flight Recorder │ Signal Dispatch     │
│   Actions are checked against policies before execution │
└─────────────────────────────────────────────────────────┘

graph TB
    subgraph Frameworks["External Frameworks"]
        LC[LangChain]
        CA[CrewAI]
        AG[AutoGen]
        OA[OpenAI]
        AN[Anthropic]
        GE[Gemini]
    end

    ADAPT[[Adapters]]

    subgraph L4["Layer 4: Intelligence"]
        SC[Self-Correction]
        SA[Semantic Analysis]
    end

    subgraph L3["Layer 3: Control Plane"]
        PE[Policy Engine]
        AL[Audit Logging]
    end

    subgraph L2["Layer 2: Infrastructure"]
        NM[Nexus Marketplace]
        OB[Observability]
    end

    subgraph L1["Layer 1: Primitives"]
        VE[Verification Engine]
        CS[Context Service]
        MS[Memory Store]
    end

    LC & CA & AG & OA & AN & GE --> ADAPT
    ADAPT --> L4
    SC & SA --> PE
    SC & SA --> AL
    PE & AL --> NM
    PE & AL --> OB
    NM & OB --> VE
    NM & OB --> CS
    NM & OB --> MS

agent-os/
├── src/agent_os/             # Core Python package
│   ├── __init__.py           # Public API (re-exports from all layers)
│   ├── stateless.py          # StatelessKernel (zero-dependency core)
│   ├── base_agent.py         # BaseAgent, ToolUsingAgent classes
│   ├── agents_compat.py      # AGENTS.md parser (OpenAI/Anthropic standard)
│   ├── cli.py                # CLI (agent-os check, review, init, etc.)
│   └── integrations/         # Framework adapters (LangChain, OpenAI, etc.)
├── modules/                  # Kernel Modules (4-layer architecture)
│   ├── primitives/           # Layer 1: Base types and failures
│   ├── cmvk/                 # Layer 1: Verification
│   ├── emk/                  # Layer 1: Episodic memory kernel
│   ├── caas/                 # Layer 1: Context-as-a-Service
│   ├── amb/                  # Layer 2: Agent message bus
│   ├── iatp/                 # Layer 2: Inter-agent trust protocol
│   ├── atr/                  # Layer 2: Agent tool registry
│   ├── observability/        # Layer 3: Prometheus + OpenTelemetry
│   ├── control-plane/        # Layer 3: THE KERNEL (policies, signals)
│   ├── scak/                 # Layer 4: Self-correcting agent kernel
│   ├── mute-agent/           # Layer 4: Face/Hands architecture
│   ├── nexus/                # Experimental: Trust exchange network
│   └── mcp-kernel-server/    # Integration: MCP protocol support
├── extensions/               # IDE & AI Assistant Extensions
│   ├── mcp-server/           # ⭐ MCP Server (Copilot, Claude, Cursor)
│   ├── vscode/               # VS Code extension
│   ├── copilot/              # GitHub Copilot extension
│   ├── jetbrains/            # IntelliJ/PyCharm plugin
│   ├── cursor/               # Cursor IDE extension
│   ├── chrome/               # Chrome extension
│   └── github-cli/           # gh CLI extension
├── examples/                 # Working examples
├── docs/                     # Documentation
├── tests/                    # Test suite (organized by layer)
├── notebooks/                # Jupyter tutorials
├── papers/                   # Research papers
└── templates/                # Policy templates

┌────────────────────────────────────────────────────────────┐
│                    AGENT HYPERVISOR                         │
│                                                            │
│   Ring 0 (Root)      ← SRE Witness required                │
│   Ring 1 (Privileged)← σ_eff > 0.95 + consensus           │
│   Ring 2 (Standard)  ← σ_eff > 0.60                        │
│   Ring 3 (Sandbox)   ← Default for unknown agents          │
│                                                            │
│   ┌──────────┐  ┌───────────┐  ┌────────────────────────┐  │
│   │  Joint    │  │  Semantic  │  │  Hash-Chained          │  │
│   │ Liability │  │   Saga     │  │  Delta Audit Trail     │  │
│   │  Engine   │  │ Orchestr.  │  │  (Tamper-Evident)      │  │
│   └──────────┘  └───────────┘  └────────────────────────┘  │
└────────────────────────────────────────────────────────────┘

pip install agent-hypervisor

from hypervisor import Hypervisor, SessionConfig, ConsistencyMode

hv = Hypervisor()

# Create a governed multi-agent session
session = await hv.create_session(
    config=SessionConfig(consistency_mode=ConsistencyMode.EVENTUAL, max_participants=5),
    creator_did="did:mesh:admin",
)

# Agents are automatically assigned privilege rings based on trust score
ring = await hv.join_session(session.sso.session_id, "did:mesh:agent-alpha", sigma_raw=0.85)
# → Ring 2 (Standard) — can execute reversible actions

# Multi-step saga with automatic timeout and compensation
saga = session.saga.create_saga(session.sso.session_id)
step = session.saga.add_step(
    saga.saga_id, "draft_email", "did:mesh:agent-alpha",
    execute_api="/api/draft", undo_api="/api/undo-draft",
    timeout_seconds=30, max_retries=2,
)

# Terminate — returns tamper-evident summary hash
summary_hash = await hv.terminate_session(session.sso.session_id)

pip install agent-os-kernel

pip install agent-os-kernel[cmvk]           # + verification
pip install agent-os-kernel[iatp]           # + inter-agent trust
pip install agent-os-kernel[observability]  # + Prometheus/OpenTelemetry
pip install agent-os-kernel[nexus]          # + trust exchange network
pip install agent-os-kernel[full]           # Everything

curl -sSL https://raw.githubusercontent.com/imran-siddique/agent-os/main/scripts/quickstart.sh | bash

iwr -useb https://raw.githubusercontent.com/imran-siddique/agent-os/main/scripts/quickstart.ps1 | iex

from agent_os import stateless_execute

# Execute with policy enforcement
result = await stateless_execute(
    action="database_query",
    params={"query": "SELECT * FROM users"},
    agent_id="analyst-001",
    policies=["read_only"]
)

from agent_os import KernelSpace, AgentSignal, PolicyRule

kernel = KernelSpace()

# Create agent context with VFS
ctx = kernel.create_agent_context("agent-001")
await ctx.write("/mem/working/task.txt", "analyze this data")

# Policy enforcement
from agent_os import PolicyEngine
engine = PolicyEngine()
engine.add_rule(PolicyRule(name="no_sql_injection", pattern="DROP|DELETE|TRUNCATE"))

# Requires: pip install agent-os-kernel[full]
from agent_os import SignalDispatcher, AgentSignal

dispatcher = SignalDispatcher()
dispatcher.signal(agent_id, AgentSignal.SIGSTOP)  # Pause
dispatcher.signal(agent_id, AgentSignal.SIGCONT)  # Resume
dispatcher.signal(agent_id, AgentSignal.SIGKILL)  # Terminate

# Requires: pip install agent-os-kernel[full]
from agent_os import AgentVFS

vfs = AgentVFS(agent_id="agent-001")
vfs.write("/mem/working/task.txt", "Current task")
vfs.read("/policy/rules.yaml")  # Read-only from user space

# LangChain
from agent_os.integrations import LangChainKernel
governed = LangChainKernel().wrap(my_chain)

# OpenAI Assistants
from agent_os.integrations import OpenAIKernel
governed = OpenAIKernel().wrap_assistant(assistant, client)

# Semantic Kernel
from agent_os.integrations import SemanticKernelWrapper
governed = SemanticKernelWrapper().wrap(sk_kernel)

# CrewAI
from agent_os.integrations import CrewAIKernel
governed = CrewAIKernel().wrap(my_crew)

# AutoGen
from agent_os.integrations import AutoGenKernel
governed = AutoGenKernel().wrap(autogen_agent)

# OpenAI Agents SDK
from agent_os.integrations import OpenAIAgentsSDKKernel
governed = OpenAIAgentsSDKKernel().wrap(agent)

# Run carbon auditor with full observability
cd examples/carbon-auditor
cp .env.example .env  # Optional: add API keys
docker-compose up

# Open dashboards
open http://localhost:3000  # Grafana (admin/admin)
open http://localhost:16686 # Jaeger traces

# Requires: pip install agent-os-kernel[full]
from atr import ToolRegistry, tool

@tool(name="safe_http", description="Rate-limited HTTP requests")
async def safe_http(url: str) -> dict:
    # Tool is automatically registered and sandboxed
    ...

registry = ToolRegistry()
registry.register(safe_http)

# Generate schemas for any LLM
openai_tools = registry.to_openai_schema()
anthropic_tools = registry.to_anthropic_schema()

# Requires: pip install agent-os-kernel[full]
from amb_core import MessageBus, Message

bus = MessageBus()
await bus.subscribe("tasks", handler)
await bus.publish("tasks", Message(payload={"task": "analyze"}))

# Check files for safety violations
agentos check src/app.py
# ✓ src/app.py: No violations
# OR
# ⚠️  2 violation(s) found in src/app.py:
#   Line 12: DROP TABLE users;
#     Violation: Destructive SQL: DROP operation detected
#     Policy: block-destructive-sql

# Check staged git files (ideal for pre-commit hooks)
agentos check --staged
# ✓ No violations in staged files

# Machine-readable JSON output (for CI pipelines)
agentos check src/app.py --format json

# CI mode (no colors, strict exit codes)
agentos check --staged --ci

# Initialize Agent OS in a project
agentos init
# Initialized Agent OS in .agents/
#   - agents.md: Agent instructions (OpenAI/Anthropic standard)
#   - security.md: Kernel policies (Agent OS extension)
#   - Template: strict

# Choose a permissive or audit-only template
agentos init --template permissive
agentos init --template audit

# Overwrite an existing .agents/ directory
agentos init --force

# Enable kernel governance and verify the configuration
agentos secure
# Securing agents in .
#   [PASS] kernel version
#   [PASS] signals defined
#   [PASS] policies defined
# Security configuration valid.

# Audit agent security configuration
agentos audit
# Auditing .
#   [OK] agents.md
#   [OK] security.md
# No issues found.

# JSON output for CI
agentos audit --format json

# Show kernel status (version, installed packages)
agentos status
# Agent OS Kernel Status
# ========================================
#   Version: 1.2.0
#   Status: Installed
#   Project: /home/user/myproject
#   Agents: Configured (.agents/ found)

# Multi-model code review with CMVK consensus
agentos review src/app.py --cmvk
# 🔍 Reviewing src/app.py with CMVK...
# Multi-Model Review (3 models):
#   ✅ gpt-4: No issues
#   ⚠️  claude-sonnet-4: 1 potential issue(s)
#   ✅ gemini-pro: No issues
# Consensus: 67%

# Specify models
agentos review src/app.py --cmvk --models "gpt-4,claude-sonnet-4"

# Validate policy YAML files
agentos validate
#   Checking .agents/policy.yaml... OK
# ✓ All 1 policy file(s) valid.

# Validate specific files in strict mode
agentos validate policies/*.yaml --strict

# Install git pre-commit hook
agentos install-hooks
# ✓ Installed pre-commit hook: .git/hooks/pre-commit
# Agent OS will now check staged files before each commit.

# Append to an existing hook
agentos install-hooks --append

# Start the HTTP API server
agentos serve --port 8080
# Agent OS API server starting on 0.0.0.0:8080
# Endpoints:
#   GET  /health              Health check
#   GET  /status              Kernel status
#   GET  /agents              List agents
#   POST /agents/{id}/execute  Execute agent action

# Output Prometheus-style metrics
agentos metrics
# # HELP agentos_policy_violations_total Total policy violations.
# # TYPE agentos_policy_violations_total counter
# agentos_policy_violations_total 0
# ...

# Quick install via npx
npx agentos-mcp-server

{
  "mcpServers": {
    "agentos": {
      "command": "npx",
      "args": ["-y", "agentos-mcp-server"]
    }
  }
}

# Install from source
git clone https://github.com/imran-siddique/agent-os.git
cd agent-os
pip install -e .

# Check what's installed
python -c "from agent_os import check_installation; check_installation()"

# Install everything
pip install -e ".[full]"

# Run PowerShell as Administrator, or use --user flag
pip install --user -e .

# Build with Dockerfile (no Docker Compose needed for simple tests)
docker build -t agent-os .
docker run -it agent-os python examples/demo-app/demo.py

# Most tests work without API keys — mock mode is default
pytest tests/ -v

# For real LLM tests, set environment variables
export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...

git clone https://github.com/imran-siddique/agent-os.git
cd agent-os
pip install -e ".[dev]"
pytest