Agentic Loop Memory Server ♾️

The industry-standard persistent memory and state manager for long-running agentic workflows.

Enable any AI model—especially smaller ones with limited context windows—to function with the persistence of high-end models. This project works as a two-part ecosystem: an MCP Server for state management and an Agent Skill for orchestration.

🛠 Complete Setup (Required)

For the best experience, you must install both the orchestration skill and the MCP server.

1. Install the Skill

Install instructions into your AI agent (Claude Code, Cursor, etc.):

npx skills add meharajM/agent-loop-mcp --yes

2. Configure the MCP Server

Add the following to your `mcp_config.json`:

{
  "mcpServers": {
    "agent-loop": {
      "command": "npx",
      "args": ["-y", "@mhrj/mcp-agent-loop"]
    }
  }
}

🌟 Why this approach is unique

Unlike passive memory tools, this is an Active State Manager. It monitors word counts to trigger compaction cycles and enforces a "Self-Healing Strategy" on every failure, preventing AI agents from getting stuck in mindless loops.

📂 Project Structure

• src/: TypeScript source for the MCP server.
• skills/agentic-loop/SKILL.md: The instruction manual for the AI.
• build/: JavaScript artifacts.

📄 License

ISC