MemoVault
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MEMOVAULT_DATA_DIR | No | The directory path where memory data will be stored. | ./memovault_data |
| MEMOVAULT_LLM_BACKEND | No | The LLM backend to use, typically 'openai' or 'ollama'. | |
| MEMOVAULT_OPENAI_MODEL | No | The OpenAI model to use (e.g., gpt-4o-mini). | gpt-4o-mini |
| MEMOVAULT_MEMORY_BACKEND | No | The storage backend for memories, either 'vector' for semantic retrieval or 'simple' for JSON storage. | |
| MEMOVAULT_OPENAI_API_KEY | No | Your OpenAI API key, required if using the 'openai' backend. | |
| MEMOVAULT_EMBEDDER_BACKEND | No | The backend used for generating embeddings (e.g., 'openai', 'ollama', or 'sentence_transformer'). |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| add_memoryA | Store new information in memory. Use this to remember facts, preferences, events, or any important information the user wants to persist across sessions. Args: content: The information to remember memory_type: Optional type (fact, preference, event, opinion, procedure, personal) Returns: Confirmation message with the memory ID |
| search_memoriesB | Search for relevant memories. Use this to find stored information related to a topic or question. Args: query: What to search for top_k: Maximum number of results (default: 5) Returns: Dictionary with matching memories |
| chat_with_memoryA | Chat with memory-enhanced responses. Use this for questions where stored memories might provide context. The response will incorporate relevant memories automatically. Args: query: User's question or message top_k: Number of memories to use as context (default: 5) Returns: AI response enhanced with relevant memories |
| get_memoryB | Retrieve a specific memory by ID. Args: memory_id: The unique identifier of the memory Returns: The memory content and metadata |
| delete_memoryC | Remove a specific memory. Args: memory_id: The unique identifier of the memory to delete Returns: Confirmation message |
| list_memoriesC | Show recent memories. Args: limit: Maximum number of memories to return (default: 10) Returns: Dictionary with list of recent memories |
| clear_memoriesA | Clear all stored memories. Warning: This permanently deletes all memories! Returns: Confirmation message |
| memory_statusB | Get the current status of the memory system. Returns: Dictionary with status information |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose with no overlap. For example, add_memory stores new information, get_memory retrieves a specific memory by ID, search_memories finds relevant memories by query, and chat_with_memory uses memories to enhance responses. The descriptions reinforce these distinct roles, making tool selection unambiguous.
All tool names follow a consistent verb_noun pattern with snake_case (e.g., add_memory, delete_memory, list_memories). The naming is predictable and readable throughout the set, with no deviations in style or convention.
With 8 tools, the count is well-scoped for a memory management server. It covers core operations like CRUD (add, get, delete, list), search, chat integration, status checks, and clearing, with each tool earning its place without feeling excessive or insufficient.
The tool set provides complete coverage for memory management, including CRUD operations (add_memory, get_memory, delete_memory, list_memories), search capabilities (search_memories), integration (chat_with_memory), system management (clear_memories, memory_status). There are no obvious gaps, and agents can handle full memory lifecycles without dead ends.