MCP Memory Gateway
Local-first context engineering layer that persists agent decisions, generates prevention rules from failures, and injects relevan
Captures feedback signals from AI agent sessions, validates and promotes them to searchable memories stored in JSONL and LanceDB vectors, and generates prevention rules from repeated failures. Provides recall tools that inject relevant past context at session start, plus DPO/KTO pair export for optional fine-tuning. Works with any MCP-compatible agent including Claude, Codex, Gemini, and Cursor.
Source
Repository: https://github.com/igorganapolsky/thumbgate
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