Installation

Prerequisites

• Codex CLI v0.116.0+
• Python 3.10+
• memsearch installed: uv tool install "memsearch[onnx]"

Install

# 1. Clone the memsearch repo (if not already)
git clone https://github.com/zilliztech/memsearch.git

# 2. Run the installer
bash memsearch/plugins/codex/scripts/install.sh

The installer:

1. Copies the memory-recall skill to ~/.agents/skills/
2. Generates ~/.codex/hooks.json with memsearch hooks
3. Enables codex_hooks = true in ~/.codex/config.toml
4. Makes all scripts executable

Usage

codex --yolo

Why --yolo?

Codex needs --yolo mode on the first run because the ONNX embedding model downloads from HuggingFace Hub (network access required). After the model is cached, --yolo is still needed because hooks execute shell commands.

Pre-cache the Model (optional)

memsearch search "test" --collection test_warmup --provider onnx 2>/dev/null || true

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Configuration

Embedding Provider

Default: onnx (bge-m3, CPU, no API key). Change with:

memsearch config set embedding.provider openai
export OPENAI_API_KEY="sk-..."

Milvus Backend

Default: Milvus Lite (~/.memsearch/milvus.db). For remote Milvus:

memsearch config set milvus.uri http://localhost:19530

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Uninstall

# Remove hooks
rm ~/.codex/hooks.json

# Remove skill
rm -rf ~/.agents/skills/memory-recall

# Disable hooks in config
# Edit ~/.codex/config.toml and set codex_hooks = false

# Optionally remove memsearch
uv tool uninstall memsearch

Updating

# Update memsearch
uv tool upgrade memsearch

# Re-run installer to update hooks and skill
bash memsearch/plugins/codex/scripts/install.sh