# Store Memory with Context
I'll help you store information in your MCP Memory Service with proper context and tagging. This command captures the current session context and stores it as a persistent memory that can be recalled later.
## What I'll do:
1. **Detect Current Context**: I'll analyze the current working directory, recent files, and conversation context to understand what we're working on.
2. **Capture Memory Content**: I'll take the provided information or current session summary and prepare it for storage.
3. **Add Smart Tags**: I'll automatically generate relevant tags based on:
- Machine hostname (source identifier)
- Current project directory name
- Programming languages detected
- File types and patterns
- Any explicit tags you provide
4. **Store with Metadata**: I'll include useful metadata like:
- Machine hostname for source tracking
- Timestamp and session context
- Project path and git repository info
- File associations and dependencies
## Usage Examples:
```bash
claude /memory-store "We decided to use SQLite-vec instead of ChromaDB for better performance"
claude /memory-store --tags "decision,architecture" "Database backend choice rationale"
claude /memory-store --type "note" "Remember to update the Docker configuration after the database change"
```
## Implementation:
I'll store the memory directly to your MCP Memory Service at `https://memory.local:8443/`. The memory will be saved automatically without confirmation prompts.
The content will be stored with automatic context detection:
- **Machine Context**: Hostname automatically added as tag (e.g., "source:your-machine-name")
- **Project Context**: Current directory, git repository, recent commits
- **Session Context**: Current conversation topics and decisions
- **Technical Context**: Programming language, frameworks, and tools in use
- **Temporal Context**: Date, time, and relationship to recent activities
The service endpoint is configured at:
- **Main endpoint**: `https://memory.local:8443/`
- **API endpoint**: `https://memory.local:8443/api/memories`
I'll use the correct curl syntax with `-k` flag for HTTPS, proper JSON payload formatting, and automatic client hostname detection using the `X-Client-Hostname` header.
## Arguments:
- `$ARGUMENTS` - The content to store as memory, or additional flags:
- `--tags "tag1,tag2"` - Explicit tags to add
- `--type "note|decision|task|reference"` - Memory type classification
- `--project "name"` - Override project name detection
- `--private` - Mark as private/sensitive content
I'll store the memory automatically without asking for confirmation. The memory will be saved immediately using proper JSON formatting with the curl command. You'll receive a brief confirmation showing the content hash and applied tags after successful storage.