agentic-looplisted

# Agentic Loop Memory Server Skill ♾️ **The industry-standard persistent memory for long-running agentic workflows.** > [!IMPORTANT] > **Prerequisite:** This skill requires the \`@mhrj/mcp-agent-loop\` MCP server to be installed and active in your agent's configuration. ## Setup Instructions To use this skill, ensure you have added the following to your \`mcp_config.json\` (e.g., in Claude Desktop, Cursor, or Windsurf): \`\`\`json { "mcpServers": { "agent-loop": { "command": "npx", "args": ["-y", "@mhrj/mcp-agent-loop"] } } } \`\`\` ## How it Works This skill connects you to the \`@mhrj/mcp-agent-loop\` server. It solves the "Goldfish Memory" problem in AI agents by providing a structured, self-compacting memory system. Unlike simple vector-search tools, this is an **active state manager** designed specifically for smaller models (like Gemini Flash or GPT-4o-mini) that need to perform complex tasks over hours or days without crashing. ## Why this is better than other memory skills: - **Zero-Dependency Transparency**: Your memory is just a Markdown file. No hidden vector databases or opaque formats. You can read/edit your own "brain" anytime. - **Active Context Compaction**: Instead of just "searching", the server warns you when your context is getting full and guides you through a summarize-and-compress cycle. - **Mandatory Self-Healing**: It prevents you from getting stuck in "infinite retry loops" by requiring a strategy for every failure. - *