Merge pull request #9807 from rwnalds/add-engram

Add rwnalds/engram to Knowledge & Memory

README.md

@@ -2193,6 +2193,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [roampal-ai/roampal-core](https://github.com/roampal-ai/roampal-core) [![roampal-core MCP server](https://glama.ai/mcp/servers/roampal-ai/roampal-core/badges/score.svg)](https://glama.ai/mcp/servers/roampal-ai/roampal-core) 🐍 🏠 - Outcome-based persistent memory for AI coding tools. Memories that help get promoted, memories that mislead get demoted. Works with Claude Code and OpenCode via hooks + MCP.
 - [roomi-fields/notebooklm-mcp](https://github.com/roomi-fields/notebooklm-mcp) [![notebooklm-mcp MCP server](https://glama.ai/mcp/servers/@roomi-fields/notebooklm-mcp/badges/score.svg)](https://glama.ai/mcp/servers/@roomi-fields/notebooklm-mcp) 📇 🏠 🍎 🪟 🐧 - Full automation of Google NotebookLM — Q&A with citations, audio podcasts, video, content generation, source management, and notebook library. MCP + HTTP REST API.
 - [rushikeshmore/CodeCortex](https://github.com/rushikeshmore/CodeCortex) [![codecortex MCP server](https://glama.ai/mcp/servers/@rushikeshmore/codecortex/badges/score.svg)](https://glama.ai/mcp/servers/@rushikeshmore/codecortex) 📇 🏠 🍎 🪟 🐧 - Persistent codebase knowledge layer for AI coding agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) via tree-sitter native parsing (28 languages) and serves via MCP. 14 tools, ~85% token reduction. Works with Claude Code, Cursor, Codex, and any MCP client.
+- [rwnalds/engram](https://github.com/rwnalds/engram) [![rwnalds/engram MCP server](https://glama.ai/mcp/servers/rwnalds/engram/badges/score.svg)](https://glama.ai/mcp/servers/rwnalds/engram) 📇 🏠 - Second brain your agents read and write, over a git-backed markdown vault. Authority-aware search ranks superseded and archived notes below live ones (from frontmatter, no vector DB), so agents quote the current doc, not the dead one. Per-agent read-only or write tokens, a git audit trail of every change with diffs, a knowledge-graph dashboard, and Obsidian compatibility.
 - [s60yucca/mnemos](https://github.com/s60yucca/mnemos) [![s60yucca/mnemos MCP server](https://glama.ai/mcp/servers/s60yucca/mnemos/badges/score.svg)](https://glama.ai/mcp/servers/s60yucca/mnemos) 🏎️ 🏠 🍎 🪟 🐧 - Persistent memory engine for AI coding agents. Stores architecture decisions, bug root causes, and project conventions across sessions. Single Go binary with embedded SQLite, FTS5 search, context assembly within token budgets, and autopilot setup for Claude Code, Kiro, and Cursor.
 - [SagaPeak/artifacta-mcp](https://github.com/SagaPeak/artifacta-mcp) [![SagaPeak/artifacta-mcp MCP server](https://glama.ai/mcp/servers/SagaPeak/artifacta-mcp/badges/score.svg)](https://glama.ai/mcp/servers/SagaPeak/artifacta-mcp) 🎖️ 📇 🐍 ☁️ 🍎 🪟 🐧 - The artifact store for AI agents. Every output your agents produce — persisted, retrievable, shareable. Across runs, sessions, and tools. Session/agent metadata, content-hash dedup, expiring share links; 11 tools with path-confined uploads and destructive actions gated by default. TypeScript (`npx @artifacta-mcp/mcp`) and Python (`pipx run artifacta-mcp`).
 - [SAIHM-Admin/saihm-mcp](https://github.com/SAIHM-Admin/saihm-mcp) [![SAIHM-Admin/saihm-mcp MCP server](https://glama.ai/mcp/servers/SAIHM-Admin/saihm-mcp/badges/score.svg)](https://glama.ai/mcp/servers/SAIHM-Admin/saihm-mcp) 📇 ☁️ 🏠 🍎 🪟 🐧 - Sovereign, encrypted, persistent memory for AI agents. Eight MCP tools — remember, recall, forget (GDPR Art. 17 erasure), share. Anchored on COTI V2 mainnet. Apache-2.0. Install: `npx -y @saihm/mcp-server`.