AgentHelm

The Control Plane for Autonomous AI Agent Fleets

AgentHelm is the control plane that keeps autonomous AI agents safe in production. It wraps any agent framework (LangGraph, CrewAI, custom Python/Node fleets, Claude Code, Cursor) with human-in-the-loop approvals, audit trails, budget guardrails, fail-closed safety, and a shared, versioned Project Brain so agents stay accountable, on-budget, and recoverable.

🧠 The Project Brain Loop

graph TD
    A[Agent Starts Task] --> B[Get Rich Context from Project Brain]
    B --> C[Agent Executes Task]
    C --> D[Propose New Knowledge/Decisions]
    D --> E[Brain Compiler Validates & Resolves Conflicts]
    E --> F[Update Project Brain Release]
    F --> A

1. Get Context: On startup, an agent fetches versioned, compiled architecture & database context.
2. Execute Safely: Agent operates within token budgets and Telegram HITL safety guardrails.
3. Propose Knowledge: As agents discover schemas or make design trade-offs, they propose knowledge entries.
4. Compile & Evolve: The Brain Compiler verifies evidence, resolves conflicts, and releases the next Project Brain version.

⚡ 60-Second Setup: Model Context Protocol (MCP)

Plug AgentHelm directly into Cursor, Claude Code, or Claude Desktop:

Add to .cursor/mcp.json or claude_desktop_config.json

{
  "mcpServers": {
    "agenthelm": {
      "command": "npx",
      "args": ["-y", "agenthelm-mcp"],
      "env": {
        "AGENTHELM_CONNECT_KEY": "ahe_live_YOUR_KEY_HERE",
        "AGENTHELM_PROJECT": "your-project-name"
      }
    }
  }
}

Exposed MCP Tools

• get_context: Query versioned project architecture, database schemas, and conventions.
• propose_knowledge: Propose new engineering decisions and codebase discoveries.
• get_history: Audit version history logs, diffs, and decision trace blame.

🚀 Programmatic SDKs

Python SDK

pip install agenthelm-sdk

from agenthelm import Agent

# Connect to control plane and fetch project brain context
agent = Agent(key="ahe_live_...", name="Architect Agent", project="My App")

# Get context for database schema
context = agent.get_context(category="database")
print("Project Context:", context.entries)

# Propose new knowledge to the Brain Compiler
agent.propose_knowledge(
    summary="Migrate authentication from JWT to Session Cookies",
    decisions=["Use session IDs mapped to Redis backend"],
    files_modified=["lib/auth.ts", "middleware.ts"],
    confidence=95
)

Node.js SDK

npm install agenthelm-node-sdk

import { Agent } from 'agenthelm-node-sdk';

const agent = new Agent({ 
  key: 'ahe_live_...', 
  name: 'Support Bot',
  project: 'My App' 
});

agent.log('Analyzing sentiment...', 'info');
agent.output({ score: 0.92 }, 'sentiment_results');

📲 Human-in-the-Loop (HITL) Safety Gate

AgentHelm prevents autonomous catastrophic actions. Mark functions as @irreversible to trigger inline Telegram approval gates:

⚠️ Irreversible Action Requested
Agent: Cloud Architect
Action: destroy_infrastructure
Payload: {"region": "us-east-1"}

[ ✅ Approve ] [ ❌ Reject ]

🏗️ Key Architecture Pillars

• 🧠 Brain Compiler: Versioned knowledge engine resolving schema and architectural decision conflicts.
• 🔭 Fleet Observability: Real-time telemetry, token cost tracking, and execution tracing.
• 🛡️ Safety Firewall: Classification decorators (@read, @side_effect, @irreversible) with fail-closed default safety.
• ⏸️ Remote Mission Control: Pause, resume, or override agent state directly from agenthelm.online.

🌐 Dashboard & Community

• Web Dashboard: https://agenthelm.online
• Documentation: agenthelm.online/docs
• Issues & Support: GitHub Issues

⚖️ License

MIT © AgentHelm Team