diff --git a/README.md b/README.md
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+++ b/README.md
@@ -2868,6 +2868,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [vbcherepanov/total-agent-memory](https://github.com/vbcherepanov/total-agent-memory) [![vbcherepanov/total-agent-memory MCP server](https://glama.ai/mcp/servers/vbcherepanov/total-agent-memory/badges/score.svg)](https://glama.ai/mcp/servers/vbcherepanov/total-agent-memory) 🐍 🏠 🍎 🪟 🐧 - Persistent local memory for coding agents: temporal knowledge graph with fact invalidation, procedural memory, episodic recall, AST codebase ingest and cross-project analogy. 74 tools, 9 IDEs, and zero LLM or network calls in the default hot path. Reproducible benchmarks — LongMemEval R@5 95.1%, LoCoMo 0.607, BEAM 1M 0.448. `pip install total-agent-memory`
 - [samvallad33/vestige](https://github.com/samvallad33/vestige) [![samvallad33/vestige MCP server](https://glama.ai/mcp/servers/samvallad33/vestige/badges/score.svg)](https://glama.ai/mcp/servers/samvallad33/vestige) 🦀 🏠 🍎 🪟 🐧 - Local-first cognitive memory for AI agents. FSRS-6 scheduling, smart ingest, SQLite storage, portable sync, embedded dashboard, and optional Cognitive Sandwich hooks for Claude Code, Cursor, Codex, and other MCP clients.
 - [vectorize-io/hindsight](https://github.com/vectorize-io/hindsight) 🐍 ☁️ 🏠 - Hindsight: Agent Memory That Works Like Human Memory - Built for AI Agents to manage Long Term Memory
+- [vishnu-77/openreflex](https://github.com/vishnu-77/openreflex) [![vishnu-77/openreflex MCP server](https://glama.ai/mcp/servers/vishnu-77/openreflex/badges/score.svg)](https://glama.ai/mcp/servers/vishnu-77/openreflex) 🐍 🏠 🍎 🪟 🐧 - Local execution memory for AI coding agents (Claude Code, Codex CLI, Cursor, OpenCode). Lifecycle hooks record coarse task metadata into a SQLite Experience Graph (no code, commands, tool output or transcripts, and no model calls). Before a similar task it injects what worked, the relevant files and known fixes with an execution budget; during a task it recommends whether to continue, pivot or stop. MCP tools cover execution context, progress checks, outcomes, search and explanations.
 - [vornicx/Midas](https://github.com/vornicx/Midas) [![vornicx/Midas MCP server](https://glama.ai/mcp/servers/vornicx/Midas/badges/score.svg)](https://glama.ai/mcp/servers/vornicx/Midas) 🐍 📇 🏠 🍎 🪟 🐧 - Local-first memory for long-horizon AI agents with no LLM at ingest — $0 per message, zero data egress, verbatim source-traceable recall. Typed belief revision, selective forgetting, and a provenance guard that blocks memory-justified destructive actions unless user-confirmed. One `midas init` wires Claude Code, Cursor, Codex, and 6 more clients to one shared SQLite memory; local web inspector and hash-chained audit log. Benchmarked on LongMemEval/LoCoMo/BEAM with one-command repros — including published negatives. `uvx midas-memory-mcp` or `npx -y midas-memory-mcp`
 - [Abhigyan-Shekhar/Waggle-mcp](https://github.com/Abhigyan-Shekhar/Waggle-mcp) [![Abhigyan-Shekhar/Waggle-mcp MCP server](https://glama.ai/mcp/servers/Abhigyan-Shekhar/Waggle-mcp/badges/score.svg)](https://glama.ai/mcp/servers/Abhigyan-Shekhar/Waggle-mcp) 🐍 🏠 🍎 🪟 🐧 - Persistent graph memory for AI agents. Drop a conversation turn in via `observe_conversation()` and facts are auto-extracted, stored as typed graph nodes with local semantic embeddings (no API key). Supports temporal queries ("what did we decide last week?"), conflict detection, and context priming. One-command setup with `waggle-mcp init`. SQLite locally, Neo4j in production.
 - [wazionapps/nexo](https://github.com/wazionapps/nexo) [![wazionapps/nexo MCP server](https://glama.ai/mcp/servers/wazionapps/nexo/badges/score.svg)](https://glama.ai/mcp/servers/wazionapps/nexo) 🐍 🏠 - Cognitive memory for AI agents with Atkinson-Shiffrin memory model (STM/LTM/sensory register), semantic RAG, Ebbinghaus decay, trust scoring, and 76+ MCP tools.