Add khwanlabs/khwan-mcp to Knowledge & Memory

README.md

@@ -2341,6 +2341,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [kage-core/Kage](https://github.com/kage-core/Kage) [![kage-core/Kage MCP server](https://glama.ai/mcp/servers/kage-core/Kage/badges/score.svg)](https://glama.ai/mcp/servers/kage-core/Kage) 📇 🏠 🍎 🪟 🐧 - Verified, git-native memory for coding agents. Memory is plain JSON packets committed in your repo, each checked against the code it cites — hallucinated citations rejected at write, stale or changed memory withheld at recall, plus diff-time stale-catch. Local-only (BM25 + vectors), no account, no API key. `npx -y @kage-core/kage-graph-mcp install`
 - [kaliaboi/mcp-zotero](https://github.com/kaliaboi/mcp-zotero) 📇 ☁️ - A connector for LLMs to work with collections and sources on your Zotero Cloud
 - [keepgoing-dev/mcp-server](https://github.com/keepgoing-dev/mcp-server) [![mcp-server MCP server](https://glama.ai/mcp/servers/keepgoing-dev/mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/keepgoing-dev/mcp-server) 📇 🏠 🍎 🪟 🐧 - Project memory for AI coding sessions. Auto-captures checkpoints on git commits, branch switches, and inactivity, then provides re-entry briefings so AI assistants pick up where you left off. Local-first, no account required.
+- [khwanlabs/khwan-mcp](https://github.com/khwanlabs/khwan-mcp) [![khwanlabs/khwan-mcp MCP server](https://glama.ai/mcp/servers/khwanlabs/khwan-mcp/badges/score.svg)](https://glama.ai/mcp/servers/khwanlabs/khwan-mcp) 🐍 ☁️ 🍎 🪟 🐧 - Durable memory for coding agents, built around corrections. Captures the moment you correct the agent as a typed event and distils it overnight into a standing rule the next session starts with, rather than only extracting facts. An isolated brain per project instead of one blended profile. Recall and record make no model calls — your client is the model. `pip install khwan-mcp`
 - [krimto-labs/krimto](https://github.com/krimto-labs/krimto) [![krimto-labs/krimto MCP server](https://glama.ai/mcp/servers/krimto-labs/krimto/badges/score.svg)](https://glama.ai/mcp/servers/krimto-labs/krimto) 📇 🏠 - Open-source team memory layer for AI coding agents. Markdown files in git as storage, a user→team→org hierarchy as the access primitive, and one cross-vendor MCP server (Claude Code, Cursor, Codex, Gemini CLI). Hybrid SQLite + sqlite-vec retrieval. Apache-2.0.
 - [kunwar-shah/claudex](https://github.com/kunwar-shah/claudex) [![kunwar-shah/claudex MCP server](https://glama.ai/mcp/servers/kunwar-shah/claudex/badges/score.svg)](https://glama.ai/mcp/servers/kunwar-shah/claudex) 📇 🏠 🍎 🪟 🐧 - Persistent memory + FTS5 full-text search for Claude Code conversation history. Indexes `~/.claude/projects/` JSONL into SQLite, exposes 10 MCP tools (store/recall/search memories, list sessions, get summaries) plus prompts. Includes a web UI for visual exploration with themes and exports. Works with Claude Code, Cursor, Codex, Windsurf, and any MCP-compatible client. `npm install -g @kunwarshah/claudex`
 - [renezander030/agentic-task-system](https://github.com/renezander030/agentic-task-system) [![renezander030/agentic-task-system MCP server](https://glama.ai/mcp/servers/renezander030/agentic-task-system/badges/score.svg)](https://glama.ai/mcp/servers/renezander030/agentic-task-system) 📇 🏠 - Turns your task manager into agent memory: hybrid (dense + sparse + keyword, RRF) retrieval over TickTick or an Obsidian vault via a six-method adapter contract. MCP server + CLI, no vector DB to build or maintain. `npm i -g @reneza/ats-cli`