MCP 服务器

agenthelm

Shared, versioned memory and governance control plane for AI coding agents. Compiler pipeline resolves architectural decision conflicts across Claude Code, Cursor, and custom agent fleets.

README

<div align="center"> <img src="https://agenthelm.online/logo.png" width="120" alt="AgentHelm Logo" /> <h1>AgentHelm</h1> <p><strong>Shared Memory and Governance Control Plane for Autonomous AI Agent Fleets</strong></p>

AgentHelm gives AI coding agents (Claude Code, Cursor, Windsurf, custom Python/Node fleets) a shared, versioned Project Brain. Agents remember architecture, API conventions, schemas, and trade-offs across sessions instead of starting from zero.

🧠 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

Get Context: On startup, an agent fetches versioned, compiled architecture & database context.
Execute Safely: Agent operates within token budgets and Telegram HITL safety guardrails.
Propose Knowledge: As agents discover schemas or make design trade-offs, they propose knowledge entries.
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.