Skip to main content
Glama

MCP Memory Service

memory-store.md3.59 kB
# 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 use a **hybrid remote-first approach** with local fallback for reliability: ### Primary: Remote API Storage - **Try remote first**: `https://narrowbox.local:8443/api/memories` - **Real-time sync**: Changes immediately available across all clients - **Single source of truth**: Consolidated database on remote server ### Fallback: Local Staging - **If remote fails**: Store locally in staging database for later sync - **Offline capability**: Continue working when remote is unreachable - **Auto-sync**: Changes pushed to remote when connectivity returns ### Smart Sync Workflow ``` 1. Try remote API directly (fastest path) 2. If offline/failed: Stage locally + notify user 3. On reconnect: ./sync/memory_sync.sh automatically syncs 4. Conflict resolution: Remote wins, with user notification ``` 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 ### Service Endpoints: - **Primary API**: `https://narrowbox.local:8443/api/memories` - **Sync Status**: Use `./sync/memory_sync.sh status` to check pending changes - **Manual Sync**: Use `./sync/memory_sync.sh sync` for full synchronization 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.

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/doobidoo/mcp-memory-service'

If you have feedback or need assistance with the MCP directory API, please join our Discord server