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Merge pull request #1915 from roampal-ai/main

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Add roampal-ai/roampal-core to Knowledge & Memory
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Frank Fiegel
2026-04-13 19:49:29 -06:00
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@@ -1505,6 +1505,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
- [ragieai/mcp-server](https://github.com/ragieai/ragie-mcp-server) 📇 ☁️ - Retrieve context from your [Ragie](https://www.ragie.ai) (RAG) knowledge base connected to integrations like Google Drive, Notion, JIRA and more. - [ragieai/mcp-server](https://github.com/ragieai/ragie-mcp-server) 📇 ☁️ - Retrieve context from your [Ragie](https://www.ragie.ai) (RAG) knowledge base connected to integrations like Google Drive, Notion, JIRA and more.
- [remembra-ai/remembra](https://github.com/remembra-ai/remembra) [![remembra MCP server](https://glama.ai/mcp/servers/remembra-ai/remembra/badges/score.svg)](https://glama.ai/mcp/servers/remembra-ai/remembra) 🐍 📇 🏠 ☁️ 🍎 🪟 🐧 - Persistent memory layer for AI agents with entity resolution, PII detection, AES-256-GCM encryption at rest, and hybrid search. 100% on LoCoMo benchmark. Self-hosted. - [remembra-ai/remembra](https://github.com/remembra-ai/remembra) [![remembra MCP server](https://glama.ai/mcp/servers/remembra-ai/remembra/badges/score.svg)](https://glama.ai/mcp/servers/remembra-ai/remembra) 🐍 📇 🏠 ☁️ 🍎 🪟 🐧 - Persistent memory layer for AI agents with entity resolution, PII detection, AES-256-GCM encryption at rest, and hybrid search. 100% on LoCoMo benchmark. Self-hosted.
- [redleaves/context-keeper](https://github.com/redleaves/context-keeper) 🏎️ 🏠 ☁️ 🍎 🪟 🐧 - LLM-driven context and memory management with wide-recall + precise-reranking RAG architecture. Features multi-dimensional retrieval (vector/timeline/knowledge graph), short/long-term memory, and complete MCP support (HTTP/WebSocket/SSE). - [redleaves/context-keeper](https://github.com/redleaves/context-keeper) 🏎️ 🏠 ☁️ 🍎 🪟 🐧 - LLM-driven context and memory management with wide-recall + precise-reranking RAG architecture. Features multi-dimensional retrieval (vector/timeline/knowledge graph), short/long-term memory, and complete MCP support (HTTP/WebSocket/SSE).
- [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. - [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. - [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.
- [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. - [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.