TencentCloud/TencentDB-Agent-Memory
TencentDB Agent Memory is a Hermes Agent plugin providing a 4-tier progressive and local-first memory pipeline to enhance AI agents by reducing token usage and improving task success rates.
Awesome Hermes Plugins › Memory Providers
Mnemosyne provides a universal memory layer designed for AI agents, with a 'Hermes-first' approach but compatible with various agent frameworks like Claude Code, Cursor, Codex, and OpenAI's OpenWebUI. It operates with zero external dependencies, utilizing a single SQLite database for all memory operations, ensuring high performance (sub-millisecond recall) and data locality. The system offers multiple levels of memory: Working Memory, Episodic Memory, and a Triple Store for knowledge graphs, all integrated through its BEAM architecture. Mnemosyne can be integrated via its Python SDK, a CLI, or as an MCP (Model Context Protocol) server, making it versatile for different agent setups. A key feature is its included 23-tool Hermes Plugin, enabling native integration and extending agents' capabilities with robust memory management, including facts, preferences, temporal data, and entity extraction. It emphasizes security and privacy, storing all data locally and optionally encrypted, distinguishing it from cloud-dependent memory solutions. The project also highlights its high performance on AI memory benchmarks like LongMemEval and BEAM.
https://github.com/mnemosyne-oss/mnemosyne
TencentDB Agent Memory is a Hermes Agent plugin providing a 4-tier progressive and local-first memory pipeline to enhance AI agents by reducing token usage and improving task success rates.
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