Layer 3: The Framework - A deterministic kernel for zero-violation governance in agentic AI systems with POSIX-style signals, VFS, and kernel/user space separation
Project description
Agent Control Plane — Public Preview
Part of Agent OS - Kernel-level governance for AI agents
Policy-based governance for autonomous AI agents.
The Agent Control Plane provides a governance layer that sits between your AI agent and the actions it performs. Define policies in YAML or Python and the control plane enforces them deterministically before any action executes.
Installation
pip install agentmesh-control-plane
Quick Start
from agent_control_plane import AgentControlPlane
plane = AgentControlPlane()
plane.load_policy("policies.yaml")
result = await plane.execute(
action="database_query",
params={"query": "SELECT * FROM users"},
agent_id="analyst-001"
)
# Safe queries execute; destructive queries are blocked by policy
Features
- Deterministic policy enforcement (YAML or Python)
- Permission management and resource quotas
- Sandboxed execution with rollback support
- Audit logging via SQLite-based Flight Recorder
- Multi-framework support (OpenAI, LangChain, MCP, A2A)
Documentation
See docs/ for guides and CONTRIBUTING.md for development setup.
License
MIT License - see LICENSE for details.
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