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Add MemoryLayer OpenCode plugin with initial implementation and configuration files
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‎.claude-plugin/marketplace.json‎

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{
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"name": "memorylayer",
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"description": "Persistent memory system designed to work seamlessly with Claude agents. MemoryLayer proactively preserves important context before compaction and allows agents to recall relevant information on demand, ensuring critical knowledge is never lost.",
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"version": "0.0.5",
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"version": "0.0.6",
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"author": {
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"name": "scitrera.ai",
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"email": "open-source-team@scitrera.com"

‎memorylayer-cc-plugin/package.json‎

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{
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"name": "@scitrera/memorylayer-cc-plugin",
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"version": "0.0.5",
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"version": "0.0.6",
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"description": "Claude Code plugin for MemoryLayer.ai - persistent memory hooks",
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"type": "module",
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"main": "dist/src/index.js",

‎memorylayer-explorer/package.json‎

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{
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"name": "@scitrera/memorylayer-explorer",
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"version": "0.0.5",
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"version": "0.0.6",
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"private": true,
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"description": "Web UI for exploring MemoryLayer memories and graph relationships",
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"scripts": {

‎memorylayer-opencode-plugin/.gitignore‎

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node_modules/
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dist/
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*.tsbuildinfo

‎memorylayer-opencode-plugin/README.md‎

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# MemoryLayer OpenCode Plugin
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Persistent memory for [OpenCode](https://github.com/sst/opencode) sessions. Gives your AI coding agent long-term memory that survives context compaction and persists across sessions.
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## What It Does
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This plugin integrates [MemoryLayer](https://memorylayer.ai) into OpenCode via two mechanisms:
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1. **MCP Tools** (21 tools) — The MemoryLayer MCP server gives the LLM direct access to remember, recall, reflect, associate, and manage memories through the standard Model Context Protocol.
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2. **Proactive Hooks** — The plugin automatically:
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- Injects workspace briefing and user directives at session start
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- Recalls relevant memories when you ask preference/convention questions
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- Captures tool observations (file edits, searches, commands) as working memory
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- Commits working memory before context compaction
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- Cleans up sessions on exit
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## Quick Start
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### 1. Install the MemoryLayer server
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```bash
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pip install memorylayer-server
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memorylayer serve
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```
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Or with Docker:
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```bash
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docker run -d -p 61001:61001 -v memorylayer-data:/data scitrera/memorylayer-server
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```
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### 2. Configure OpenCode
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Add to your `opencode.json`:
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```json
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{
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"mcp": {
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"memorylayer": {
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"type": "local",
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"command": ["npx", "@scitrera/memorylayer-mcp-server"],
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"environment": {
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"MEMORYLAYER_URL": "{env:MEMORYLAYER_URL}",
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"MEMORYLAYER_API_KEY": "{env:MEMORYLAYER_API_KEY}"
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},
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"enabled": true
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}
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},
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"plugin": ["@scitrera/memorylayer-opencode-plugin"]
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}
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```
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### 3. Set environment variables (optional)
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```bash
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export MEMORYLAYER_URL=http://localhost:61001 # default
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export MEMORYLAYER_API_KEY=your-key # optional, for authenticated servers
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```
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### 4. Verify
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Start OpenCode and run `/memorylayer-status` to check the connection.
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## Slash Commands
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| Command | Description |
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|---------|-------------|
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| `/memorylayer-remember <content>` | Store a memory with auto-detected type and importance |
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| `/memorylayer-recall <query>` | Search memories by semantic query |
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| `/memorylayer-status` | Check connection status and workspace info |
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| `/memorylayer-setup` | Guided setup and verification |
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## How Hooks Work
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### Session Start (`experimental.chat.system.transform`)
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On first interaction, loads workspace briefing, user directives, and any existing sandbox state into the system prompt.
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### User Messages (`chat.message`)
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Detects 5 pattern categories in user messages and performs targeted recall:
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- **Preference**: "which X should we use", "what's our convention"
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- **Recall**: "remember", "what did we", "remind me"
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- **Analysis**: "review", "analyze", "status"
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- **Implementation**: "implement", "build", "fix"
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- **Error**: "error", "bug", "broken"
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### Tool Execution (`tool.execute.before` / `tool.execute.after`)
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- **Before**: Injects recalled context for edit/write and task/delegation tools
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- **After**: Silently captures observations (files, facts, concepts, intent) as working memory
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### Context Compaction (`experimental.session.compacting`)
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Commits working memory to long-term storage and checkpoints server-side sandbox state before the context window is trimmed.
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### Shell Environment (`shell.env`)
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Propagates `MEMORYLAYER_URL` and `MEMORYLAYER_API_KEY` to shell commands.
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## Configuration
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### Environment Variables
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `MEMORYLAYER_URL` | `http://localhost:61001` | MemoryLayer server URL |
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| `MEMORYLAYER_API_KEY` | — | API key (optional for local servers) |
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| `MEMORYLAYER_WORKSPACE_ID` | auto-detected | Workspace identifier (auto-detected from git repo name) |
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### Workspace Auto-Detection
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The workspace ID is automatically detected from:
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1. Git remote origin repository name
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2. Git root directory name
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3. Current working directory name
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Override with the `MEMORYLAYER_WORKSPACE_ID` environment variable.
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## Memory Types
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| Type | Description | Importance |
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|------|-------------|------------|
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| `semantic` | Facts, concepts, knowledge | 0.5-0.9 |
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| `procedural` | How-to, solutions, patterns | 0.5-0.8 |
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| `episodic` | Events, what happened | 0.5-0.7 |
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| `working` | Current task context (auto-expires) | 0.3-0.6 |
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### Common Subtypes
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`directive`, `decision`, `fix`, `solution`, `code_pattern`, `error`, `workflow`, `preference`, `problem`
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## Architecture
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```
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OpenCode
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├── MCP Server (@scitrera/memorylayer-mcp-server)
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│ └── 21 memory tools (remember, recall, reflect, etc.)
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│
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├── Plugin Hooks (@scitrera/memorylayer-opencode-plugin)
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│ ├── system.transform → session briefing injection
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│ ├── chat.message → pattern-based recall
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│ ├── tool.before → pre-tool context injection
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│ ├── tool.after → observation capture
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│ ├── session.compacting → working memory commit
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│ └── shell.env → env var propagation
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│
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└── MemoryLayer Server (memorylayer-server)
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├── Memory storage (SQLite + vector search)
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├── Knowledge graph (associations)
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├── Working memory (sessions)
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└── Context sandbox (Python execution)
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```
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## Troubleshooting
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### Server not reachable
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```bash
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# Check if server is running
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curl http://localhost:61001/health
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# Start the server
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memorylayer serve
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# Or with Docker
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docker run -d -p 61001:61001 -v memorylayer-data:/data scitrera/memorylayer-server
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```
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### MCP tools not available
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Verify `opencode.json` has the `mcp.memorylayer` configuration. Restart OpenCode after configuration changes.
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### Plugin not loading
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Ensure the plugin is listed in `opencode.json`:
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```json
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{
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"plugin": ["@scitrera/memorylayer-opencode-plugin"]
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}
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```
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## License
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Apache-2.0

‎memorylayer-opencode-plugin/opencode.example.json‎

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{
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"$schema": "https://opencode.ai/config.json",
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"mcp": {
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"memorylayer": {
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"type": "local",
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"command": ["npx", "@scitrera/memorylayer-mcp-server"],
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"environment": {
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"MEMORYLAYER_URL": "{env:MEMORYLAYER_URL}",
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"MEMORYLAYER_API_KEY": "{env:MEMORYLAYER_API_KEY}"
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},
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"enabled": true
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}
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},
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"plugin": ["@scitrera/memorylayer-opencode-plugin"]
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}

‎memorylayer-opencode-plugin/package-lock.json‎

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‎memorylayer-opencode-plugin/package.json‎

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{
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"name": "@scitrera/memorylayer-opencode-plugin",
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"version": "0.0.6",
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"description": "OpenCode plugin for MemoryLayer.ai - persistent memory hooks and context injection",
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"type": "module",
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"main": "dist/src/index.js",
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"types": "dist/src/index.d.ts",
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"scripts": {
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"build": "tsc",
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"dev": "tsc --watch",
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"prepublishOnly": "npm run build"
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},
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"author": "Scitrera LLC",
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"license": "Apache-2.0",
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"repository": {
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"type": "git",
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"url": "https://github.com/scitrera/memorylayer",
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"directory": "oss/memorylayer-opencode-plugin"
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},
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"homepage": "https://memorylayer.ai",
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"keywords": [
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"opencode",
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"memorylayer",
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"memory",
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"context",
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"persistence",
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"knowledge-graph",
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"recall",
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"agent",
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"llm",
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"ai",
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"mcp"
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],
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"dependencies": {
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"@scitrera/memorylayer-mcp-server": "file:../memorylayer-mcp-typescript"
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},
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"devDependencies": {
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"@types/node": "^20.0.0",
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"typescript": "^5.9.3"
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},
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"peerDependencies": {
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"@opencode-ai/plugin": ">=0.1.0"
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},
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"peerDependenciesMeta": {
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"@opencode-ai/plugin": {
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"optional": true
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}
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},
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"engines": {
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"node": ">=18.0.0"
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}
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}

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