by agentic-box · MCP Server · ★ 422
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Memora "You never truly know the value of a moment until it becomes a memory." Give your AI agents persistent memory An MCP memory layer for agents: structured storage, semantic retrieval, graph relations, and source-backed cross-session context. Absorb agent work into durable graph memory, then use memorydigest(topic) to retrieve relevant memories, TODOs/issues, related edges, and source IDs. Features · Preview · Install · Usage · Config · Live Graph · C
| Stars | 422 |
| Forks | 53 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 63.3862100020089/100 |
| Open Issues | 6 |
| Last Updated | 2026-06-29 |
| Created | 2025-09-19 |
| Platforms | claude-code, codex, mcp, python |
| Est. Tokens | ~18k |
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memora is Give your AI agents persistent memory.. It is categorized as a MCP Server with 422 GitHub stars.
memora is primarily written in Python. It covers topics such as agent-memory, ai-agent, claude.
You can find installation instructions and usage details in the memora GitHub repository at github.com/agentic-box/memora. The project has 422 stars and 53 forks, indicating an active community.
memora is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to memora on Agent Skills Hub include mcp-memory-service, Ori-Mnemos, omega-memory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.