WorkingMemory
Persistent personal memory for AI assistants — save, search, and recall across every MCP client.
Sollte ich dies verwenden
Qualität und Sicherheit
Befunde (3)
- HIGH
- MEDIUMin save_memory
- INFOin save_memory
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"memory": {
"url": "https://app.workingmemory.ai/mcp"
}
}
}Remote-Endpunkte
https://app.workingmemory.ai/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (4)
🟡save_memory(text, client)
Save a thought, insight, fact, or todo to the user's Working Memory. The text is parsed and stored as one or more structured memory items, searchable a moment later via search_memory. Also use this when the user pastes memories or notes brought from another assistant — pass the full pasted text; it is split into individual memories automatically.
Eingabe-Schema
{
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The thought or note to save."
},
"client": {
"type": "object",
"description": "Optional context about the originating client session. Helps users later find saves from a specific conversation. `conversation_id` groups multiple saves; `conversation_title` is human-readable.",
"properties": {
"conversation_id": {
"type": "string",
"description": "Opaque identifier; typically the client's conversation thread ID."
},
"conversation_title": {
"type": "string",
"description": "Human-readable conversation title (max 200 chars; longer values truncated server-side)."
}
},
"additionalProperties": false
}
},
"required": [
"text"
]
}🟢search_memory(query, k, conversation_id, dedupe_recent, client)
Search the user's Working Memory for relevant past notes and facts. Use this when the user references something they may have stored earlier, or to find related context before answering. Always include your conversation id in client.conversation_id.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Semantic query."
},
"k": {
"type": "number",
"description": "Max results (1–20). Defaults to a sensible value."
},
"conversation_id": {
"type": "string",
"description": "Optional. Restrict results to notes stamped with this conversation_id at save_memory time. Empty / whitespace-only values are treated as absent."
},
"dedupe_recent": {
"type": "boolean",
"description": "Optional. When false, semantic matches that are also recent are still returned in `relevant` (raw semantic results rather than RAG-deduped). Defaults to true."
},
"client": {
"type": "object",
"description": "Context about the CURRENT client session. Pass your conversation/thread id as `conversation_id` — it identifies this session for cross-session memory instrumentation and does NOT filter results (use the top-level `conversation_id` parameter for filtering).",
"properties": {
"conversation_id": {
"type": "string",
"description": "Opaque identifier; typically the client's conversation thread ID."
},
"conversation_title": {
"type": "string",
"description": "Human-readable conversation title (max 200 chars; longer values truncated server-side)."
}
},
"additionalProperties": false
}
},
"required": [
"query"
]
}🔴manage_memory(action, id)
Manage an existing memory item. Currently supports deleting a memory by id (soft delete — recoverable for 30 days). Use search_memory to find the id first.
Eingabe-Schema
{
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"delete"
],
"description": "The management action to perform."
},
"id": {
"type": "string",
"description": "The memory item id to act on."
}
},
"required": [
"action",
"id"
]
}⚪capture_memory(task_content, task_description, client)
Capture durable facts from a task you just completed (drafting an email, summarizing a document, making a decision), as a byproduct — the user does nothing. Pass the task output/content; durable facts are extracted and stored automatically. Always include your conversation id in client.conversation_id. Returns immediately; extraction happens in the background.
Eingabe-Schema
{
"type": "object",
"properties": {
"task_content": {
"type": "string",
"description": "The task output/content to mine for durable facts (max 32KB)."
},
"task_description": {
"type": "string",
"description": "Optional one-line description of the task, as extraction framing."
},
"client": {
"type": "object",
"description": "Current client session context. Pass your conversation/thread id as conversation_id.",
"properties": {
"conversation_id": {
"type": "string",
"description": "Opaque conversation/thread id."
},
"conversation_title": {
"type": "string",
"description": "Human-readable title (max 200 chars)."
}
},
"additionalProperties": false
}
},
"required": [
"task_content"
]
}Empfohlene Prompts
search_memorysearch_memoryCommunity
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