by hermes-labs-ai · MCP Server · ★ 62
A local dual-layer memory pattern for AI agents: a compact, human-readable markdown index paired with semantic retrieval from a local vector store, queried before each message. For cross-project recall where flat memory files or vector-only RAG fall short. Local-first. Reference implementation.
| Stars | 62 |
| Forks | 6 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 35.8/100 |
| Last Updated | 2026-09-28 |
| Created | 2026-03-12 |
| Platforms | claude-code, python |
| Est. Tokens | ~6k |
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zer0dex is A local dual-layer memory pattern for AI agents: a compact, human-readable markdown index paired with semantic retrieval from a local vector store, queried before each message. For cross-project recal. It is categorized as a MCP Server with 62 GitHub stars.
zer0dex is primarily written in Python. It covers topics such as agent-memory, ai-agents, ai-memory.
You can find installation instructions and usage details in the zer0dex GitHub repository at github.com/hermes-labs-ai/zer0dex. The project has 62 stars and 6 forks, indicating an active community.
zer0dex is released under the Apache-2.0 license, making it free to use and modify according to the license terms.