Opencode Mem — Data skill for Claude Code
OpenCode plugin that gives coding agents persistent memory using local vector database.
How to install Opencode Mem
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open tickernelz/opencode-mem and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Opencode Mem does
OpenCode plugin that gives coding agents persistent memory using local vector database.
Alternatives in Data
- OpenViking — Self-evolving Context Database for AI Agents 33.3k ★
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README
OpenCode Memory
[](https://www.npmjs.com/package/opencode-mem) [](https://www.npmjs.com/package/opencode-mem) [](https://www.npmjs.com/package/opencode-mem)

A persistent memory system for AI coding agents that enables long-term context retention across sessions using local vector database technology.
Visual Overview
**Project Memory Timeline:**

**User Profile Viewer:**

Core Features
Local Turso/libSQL database with native vector search, persistent project memories, automatic user profile learning, unified memory-prompt timeline, full-featured web UI, intelligent prompt-based memory extraction, multi-provider AI support (OpenAI, Anthropic), 12+ local embedding models, smart deduplication, and built-in privacy protection.
Prerequisites
This plugin uses embedded Turso/libSQL with native vector indexes (`F32_BLOB`, `vector_top_k`). No separate vector database or custom SQLite build is required.
**Recommended runtime:**
- Bun
- Standard OpenCode plugin environment
- Internet access on first use if you use the default local embedding model, because the model is downloaded by
@huggingface/transformers. - For source/development installs, run
bun installbefore building or testing. The published plugin package installs its runtime dependencies automatically through OpenCode.
**CI-tested platforms:** Linux, Windows, macOS 15 and macOS 26 on both Intel (`darwin/x64`) and Apple Silicon (`darwin/arm64`). Older macOS releases are not excluded by that matrix; they are simply outside the current GitHub-hosted runner set.
**Notes:**
- Vector embeddings are stored and searched directly in Turso/libSQL; in
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