#135135th of 193 in Skills, plugins and prompts
memsearch
Persistent semantic memory for Claude Code, Codex, OpenClaw and OpenCode agents
- Stars
- 2.8k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Sep 2026
- Language
- Python
1,023 on 31 Mar 20262,767 on 20 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Zilliz is hiring: 11 open roles
Overview
memsearch captures each agent conversation turn as an LLM-written summary in daily Markdown files, then indexes them in Milvus with hybrid search (dense vector, BM25, RRF). Plugins exist for Claude Code, Codex, DeepSeek Harness, OpenClaw and OpenCode, and a CLI and Python API allow use in custom agents. Recall runs in three layers: search, expand, then raw transcript.
Who it is for: Users of coding agents who want searchable memory across sessions and tools
Strengths
- Markdown files are the source of truth; the Milvus index is rebuildable
- One memory shared across five agent platforms
- Default local ONNX bge-m3 embeddings need no API key; Milvus Lite needs no setup
- Also exposes a CLI and Python API for custom agents
Weaknesses
- First run downloads a ~558 MB embedding model from HuggingFace
- Capture summaries call an LLM on every turn, adding model usage
- Codex install needs `codex --yolo` for ONNX network access
- Team use needs a separate Milvus server or Zilliz Cloud
What it needs
- no GPU
- Needs Milvus (Lite by default), HuggingFace Hub (model download), Python >=3.10
- Models: ONNX bge-m3, OpenAI embeddings, Ollama
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