evermemos-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| EVERMEM_API_KEY | No | EverMemOS Cloud API Key. Required for cloud mode. | |
| EVERMEM_API_URL | No | API URL. Defaults to https://api.evermind.ai if API key is set, otherwise http://localhost:8001. | |
| EVERMEM_USER_ID | No | Default user ID. | windsurf_user |
| EVERMEM_GROUP_ID | No | Default project/group ID. | windsurf_project |
| EVERMEM_API_VERSION | No | API version. | v0 |
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| store_memoryA | Save a conversation message into EverMemOS long-term memory. Use this tool when the user shares important information that should be remembered across sessions, such as: project preferences, coding conventions, architecture decisions, deployment procedures, personal preferences, etc. Args: content: The message content to remember. Be specific and include key details. role: Who sent this message - "user" for human messages, "assistant" for AI responses. sender: User ID for memory ownership. Defaults to EVERMEM_USER_ID env var. group_id: Project/group identifier to organize memories. Defaults to EVERMEM_GROUP_ID env var. flush: If True, force immediate memory extraction instead of waiting for natural conversation boundary detection. |
| search_memoryA | Search EverMemOS for relevant memories based on a natural language query. Use this tool when you need to recall past context, such as: project setup details, user preferences, previous decisions, coding patterns, deployment steps, etc. Args: query: Natural language search query describing what you're looking for. user_id: User ID to search memories for. Defaults to EVERMEM_USER_ID env var. group_id: Optional project/group filter to narrow search scope. retrieve_method: Search strategy - "keyword" (BM25, default), "vector" (semantic), "hybrid" (keyword+vector+rerank, requires rerank service), "rrf" (fusion), "agentic" (LLM-guided multi-round). top_k: Maximum number of results to return (1-20). |
| get_memoriesA | Retrieve stored memories by user ID and type. Use this tool to browse a user's memory collection without a specific search query. Args: user_id: User ID to fetch memories for. Defaults to EVERMEM_USER_ID env var. memory_type: Type of memory to retrieve - "episodic_memory" (conversation summaries), "foresight" (predicted future needs), "event_log" (atomic facts), "profile" (user profile). group_id: Optional project/group filter. limit: Maximum number of results (1-50). |
| delete_memoryA | Delete memories from EverMemOS. Use this tool when the user explicitly asks to forget or remove certain memories. This performs a soft delete. Args: user_id: User ID whose memories to delete. Defaults to EVERMEM_USER_ID env var. group_id: Optional group/project filter - only delete memories in this group. memory_type: Optional type filter - only delete this type (episodic_memory, foresight, event_log). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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