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Merge pull request #8024 from mcasdfgf/main

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Add mcp-roo-memory to Knowledge & Memory section
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Frank Fiegel
2026-06-14 18:18:55 -07:00
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@@ -1923,6 +1923,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
- [markmhendrickson/neotoma](https://github.com/markmhendrickson/neotoma) [![Neotoma MCP server](https://glama.ai/mcp/servers/markmhendrickson/neotoma/badges/score.svg)](https://glama.ai/mcp/servers/markmhendrickson/neotoma) 📇 🏠 🍎 🪟 🐧 - Deterministic state layer for AI agents. Stores versioned entities (contacts, tasks, transactions, decisions) with immutable observations, full provenance, and schema-first extraction. Local-first SQLite, cross-client memory across Claude, Cursor, ChatGPT, and OpenClaw. [Website](https://neotoma.io)
- [mattjoyce/mcp-persona-sessions](https://github.com/mattjoyce/mcp-persona-sessions) 🐍 🏠 - Enable AI assistants to conduct structured, persona-driven sessions including interview preparation, personal reflection, and coaching conversations. Built-in timer management and performance evaluation tools.
- [maxkuminov/obsidian-mcp](https://github.com/maxkuminov/obsidian-mcp) [![obsidian-mcp MCP server](https://glama.ai/mcp/servers/maxkuminov/obsidian-mcp/badges/score.svg)](https://glama.ai/mcp/servers/maxkuminov/obsidian-mcp) 🐍 🏠 🍎 🪟 🐧 - Self-hosted MCP server for Obsidian with semantic + full-text search over PostgreSQL/pgvector, wikilink graph traversal, atomic note CRUD, OAuth 2.0, and a self-describing vault guide.
- [mcasdfgf/mcp-roo-memory](https://github.com/mcasdfgf/mcp-roo-memory) 🐍 🏠 🍎 🪟 🐧 - Persistent fractal graph memory for AI coding agents via MCP. Semantic vector search, hot/cold/archive context tiers, decision tracking, and Docker-based deployment with Qdrant.
- [mem0ai/mem0-mcp](https://github.com/mem0ai/mem0-mcp) 🐍 🏠 - A Model Context Protocol server for Mem0 that helps manage coding preferences and patterns, providing tools for storing, retrieving and semantically handling code implementations, best practices and technical documentation in IDEs like Cursor and Windsurf
- [udjin-labs/mnemostack](https://github.com/udjin-labs/mnemostack) [![udjin-labs/mnemostack MCP server](https://glama.ai/mcp/servers/udjin-labs/mnemostack/badges/score.svg)](https://glama.ai/mcp/servers/udjin-labs/mnemostack) 🐍 🏠 🍎 🪟 🐧 - Durable hybrid memory for AI agents. Combines vector search, BM25, temporal retrieval, and optional Memgraph knowledge graph via reciprocal rank fusion. 6 MCP tools: health, search, answer, feedback, graph_query, graph_add_triple. Self-hosted with Qdrant backend. 82.5% strict accuracy on LoCoMo benchmark. `pip install 'mnemostack[mcp]'`
- [tverney/mcp-agent-memory](https://github.com/tverney/mcp-agent-memory) [![tverney/mcp-agent-memory MCP server](https://glama.ai/mcp/servers/tverney/mcp-agent-memory/badges/score.svg)](https://glama.ai/mcp/servers/tverney/mcp-agent-memory) 📇 🏠 🍎 - Persistent agent memory via filesystem-native consolidation daemon. Agents read/write/search memory through MCP; a background daemon handles consolidation and extraction. Works with Kiro, Claude Desktop, Cursor, and any MCP client. `npx mcp-agent-memory --setup`