OpenCode Memory

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 vector database with SQLite + HNSW (hnswlib-wasm), 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 hnswlib-node for fast vector similarity search, which requires native compilation. Ensure you have:

All platforms:

• Python 3.x
• A C++ compiler (gcc, clang, or MSVC)
• make or CMake

Platform-specific setup:

| Platform | Requirements | | ----------- | ------------------------------------------------------------------------------------------------------------------------- | | macOS | Xcode Command Line Tools: xcode-select --install | | Linux | Build essentials: sudo apt install build-essential python3 (Debian/Ubuntu) or sudo pacman -S base-devel python (Arch) | | Windows | Visual Studio Build Tools with C++ workload, or Windows Build Tools: npm install -g windows-build-tools |

Getting Started

Add to your OpenCode configuration at ~/.config/opencode/opencode.json:

{
  "plugin": ["opencode-mem"],
}

The plugin downloads automatically on next startup.

Usage Examples

memory({ mode: "add", content: "Project uses microservices architecture" });
memory({ mode: "search", query: "architecture decisions" });
memory({ mode: "profile" });
memory({ mode: "list", limit: 10 });

Access the web interface at http://127.0.0.1:4747 for visual memory browsing and management.

Configuration Essentials

Configure at ~/.config/opencode/opencode-mem.jsonc:

{
  "storagePath": "~/.opencode-mem/data",
  "userEmailOverride": "[email protected]",
  "userNameOverride": "John Doe",
  "embeddingModel": "Xenova/nomic-embed-text-v1",
  "webServerEnabled": true,
  "webServerPort": 4747,

  "autoCaptureEnabled": true,
  "autoCaptureLanguage": "auto",
  "memoryProvider": "openai-chat",
  "memoryModel": "gpt-4o-mini",
  "memoryApiUrl": "https://api.openai.com/v1",
  "memoryApiKey": "sk-...",
  "memoryTemperature": 0.3,

  "showAutoCaptureToasts": true,
  "showUserProfileToasts": true,
  "showErrorToasts": true,

  "userProfileAnalysisInterval": 10,
  "maxMemories": 10,

  "compaction": {
    "enabled": true,
    "memoryLimit": 10,
  },
  "chatMessage": {
    "enabled": true,
    "maxMemories": 3,
    "excludeCurrentSession": true,
    "maxAgeDays": undefined,
    "injectOn": "first",
  },
}

API Key Formats:

"memoryApiKey": "sk-..."
"memoryApiKey": "file://~/.config/opencode/api-key.txt"
"memoryApiKey": "env://OPENAI_API_KEY"

Full documentation available in this README.

Development & Contribution

Build and test locally:

bun install
bun run build
bun run typecheck
bun run format

This project is actively seeking contributions to become the definitive memory plugin for AI coding agents. Whether you are fixing bugs, adding features, improving documentation, or expanding embedding model support, your contributions are critical. The codebase is well-structured and ready for enhancement. If you hit a blocker or have improvement ideas, submit a pull request - we review and merge contributions quickly.

License & Links

MIT License - see LICENSE file

• Repository: https://github.com/tickernelz/opencode-mem
• Issues: https://github.com/tickernelz/opencode-mem/issues
• OpenCode Platform: https://opencode.ai

Inspired by opencode-supermemory