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@@ -1071,7 +1071,6 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [dodopayments/contextmcp](https://github.com/dodopayments/context-mcp) 📇 ☁️ 🏠 - Self-hosted MCP server that indexes documentation from various sources and serves it to AI Agents with semantic search.
 - [doobidoo/MCP-Context-Provider](https://github.com/doobidoo/MCP-Context-Provider) 📇 🏠 - Static server that provides persistent tool-specific context and rules for AI models
 - [doobidoo/mcp-memory-service](https://github.com/doobidoo/mcp-memory-service) 📇 🏠 - Universal memory service providing semantic search, persistent storage, and autonomous memory consolidation
-- [engram-sdk](https://github.com/tstockham96/engram) 📇 🏠 🍎 🪟 🐧 - Universal memory layer for AI agents with vector search, automatic consolidation, bi-temporal recall, and MCP tools. Zero-dependency Node.js server, works with any LLM provider.
 - [entanglr/zettelkasten-mcp](https://github.com/entanglr/zettelkasten-mcp) 🐍 🏠 - A Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, and search atomic notes through Claude and other MCP-compatible clients.
 - [g1itchbot8888-del/agent-memory](https://github.com/g1itchbot8888-del/agent-memory) 🐍 🏠 - Three-layer memory system for agents (identity/active/archive) with semantic search, graph relationships, conflict detection, and LearningMachine. Built by an agent, for agents. No API keys required.
 - [ErebusEnigma/context-memory](https://github.com/ErebusEnigma/context-memory) 🐍 🏠 🍎 🪟 🐧 - Persistent, searchable context storage across Claude Code sessions using SQLite FTS5. Save sessions with AI-generated summaries, two-tier full-text search, checkpoint recovery, and a web dashboard.
@@ -1116,6 +1115,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [topoteretes/cognee](https://github.com/topoteretes/cognee/tree/dev/cognee-mcp) 📇 🏠 - Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources
 - [timowhite88/farnsworth-syntek](https://github.com/timowhite88/farnsworth-syntek) 📇 ☁️ - 7-layer recursive agent memory with context branching, holographic recall, dream consolidation, and on-chain persistence. MCP-native with 10 tools for persistent agent cognition.
 - [topskychen/tilde](https://github.com/topskychen/tilde) 🐍 🏠 - Your AI agents' home directory — privacy-first MCP server for portable AI identity. Configure once, use everywhere. It supports profile management, skills, resume import, and team sync.
+- [tstockham96/engram](https://github.com/tstockham96/engram) 📇 🏠 🍎 🪟 🐧 - Intelligent agent memory with semantic recall, automatic consolidation, contradiction detection, and bi-temporal knowledge graph. 80% on LOCOMO benchmark using 96% fewer tokens than full-context approaches.
 - [TeamSafeAI/LIFE](https://github.com/TeamSafeAI/LIFE) 🐍 🏠 - Persistent identity architecture for AI agents. 16 MCP servers covering drives, emotional relationships, semantic memory with decay, working threads, learned patterns, journal, genesis (identity discovery), creative collision engine, forecasting, and voice. Zero dependencies beyond Python 3.8. Built across 938 conversations.
 - [unibaseio/membase-mcp](https://github.com/unibaseio/membase-mcp) 📇 ☁️ - Save and query your agent memory in distributed way by Membase
 - [upstash/context7](https://github.com/upstash/context7) 📇 ☁️ - Up-to-date code documentation for LLMs and AI code editors.