MemRL
Verified IntegrationClient Configuration
— Connect MemRL to Claude Desktop or Cursor in seconds{
"mcpServers": {
"memrl": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memrl"
],
"env": {}
}
}
}~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows).System Overview
Provides AI agents with a persistent, reinforcement-learning-powered memory system for continuous improvement.
7/23/2026
Open Source
stdio / SSE RPC
Frequently Asked Questions
Architecture and operational details for MemRL
MemRL uses a sophisticated learning loop involving episodic memory capture, semantic retrieval, and reinforcement learning. It applies feedback, Bellman propagation, and temporal credit to boost useful memories and similar ones, while unhelpful or stale memories decay, ensuring the AI's knowledge base evolves and stays relevant.
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