memsearch OpenCode Plugin

Semantic memory search for OpenCode — gives your AI assistant persistent memory across sessions with zero user intervention.

Features

• Auto-capture: Summarizes each conversation turn and saves to daily .md files
• Semantic search: Hybrid search (BM25 + dense vectors + RRF) via Milvus
• Three-layer recall: Search → Expand → Transcript (progressive detail)
• Cold-start context: Injects recent memories into new sessions automatically
• Per-project isolation: Each project gets its own Milvus collection
• ONNX embeddings: CPU-only bge-m3 model, no API key required

Quick Start

Prerequisites

# Install memsearch with ONNX embeddings
uv tool install 'memsearch[onnx]'
# or: pip install 'memsearch[onnx]'

Install from npm (recommended)

// In ~/.config/opencode/opencode.json
{
  "plugin": ["@zilliz/memsearch-opencode"]
}

Install from Source (development)

# Clone the repo
git clone https://github.com/zilliztech/memsearch.git
cd memsearch

# Run the installer
bash plugins/opencode/install.sh

Manual Install

# 1. Symlink the plugin
mkdir -p ~/.config/opencode/plugins
ln -sf /path/to/memsearch/plugins/opencode/index.ts ~/.config/opencode/plugins/memsearch.ts

# 2. Symlink the skill (optional, for !memory-recall)
mkdir -p ~/.agents/skills
ln -sf /path/to/memsearch/plugins/opencode/skills/memory-recall ~/.agents/skills/memory-recall

Architecture

OpenCode Session
    ├── chat.message hook ──→ Detect turn completion
    │                              │
    │                              ├── Extract last turn from SQLite
    │                              ├── Summarize via LLM (third-person notes)
    │                              └── Append to .memsearch/memory/YYYY-MM-DD.md
    │                                     │
    │                                     └── memsearch index (background)
    │
    ├── system.transform hook ──→ Inject recent memories
    │
    └── Tools
        ├── memory_search ──→ memsearch search (hybrid BM25+dense)
        ├── memory_get    ──→ memsearch expand (full context)
        └── memory_transcript ──→ parse-transcript.py (SQLite reader)

Recall Memories

Manual invocation — explicitly invoke the skill with a query:

/memory-recall what was the auth approach we discussed?

Auto invocation — just ask naturally, the LLM auto-invokes memory tools when it senses the question needs history:

We discussed the authentication flow before, what was the approach?

Tools

| Tool | Description | |------|-------------| | memory_search | Semantic search over past memories. Returns ranked chunks. | | memory_get | Expand a chunk hash to see the full markdown section. | | memory_transcript | Read original conversation from OpenCode SQLite DB. |

Memory Files

Memory is stored as markdown in <project>/.memsearch/memory/:

.memsearch/
└── memory/
    ├── 2026-03-25.md
    └── 2026-03-26.md

Each file contains timestamped entries with bullet-point summaries:

# 2026-03-26

## Session 14:30

### 14:30
<!-- session:ses_abc123 db:~/.local/share/opencode/opencode.db -->
- User asked about the authentication flow.
- Assistant explained the OAuth2 implementation in auth.ts.
- Assistant modified the token refresh logic in refresh.ts.

Configuration

The plugin uses ONNX embeddings by default (no API key needed). To use a different provider:

memsearch config set embedding.provider openai
# Set the API key in your environment
export OPENAI_API_KEY=sk-...

How It Works

1. Capture: After each conversation turn, the plugin extracts the user+assistant exchange, summarizes it via LLM, and appends to a daily markdown file.

2. Index: The markdown files are indexed by memsearch into a Milvus collection (Milvus Lite by default, runs in-process).

3. Recall: When the assistant needs historical context, it calls memory_search to find relevant chunks. Results can be expanded with memory_get or drilled into with memory_transcript.

4. Cold-start: At session start, recent memory bullets are injected into the system prompt so the assistant has immediate context.

Differences from Other Plugins

| Feature | Claude Code | OpenCode | OpenClaw | |---------|-------------|----------|----------| | Session storage | JSONL | SQLite | JSONL | | Hook system | Shell scripts | TypeScript hooks | JS API | | Summarizer | claude -p --model haiku | opencode prompt | openclaw agent | | Context injection | SessionStart hook | system.transform | before_agent_start | | Skill context | context: fork | N/A (no fork) | N/A |