MemoryPlugin MCP server

What tools does MemoryPlugin expose? (14)

Read from the live server. Click any tool for its input schema.

• store_memorySave information to the user's MemoryPlugin account. MemoryPlugin lets users build persistent memory across AI conversations. WHEN TO USE: When the user asks to remember something, or confirms that a specific fact, preference, decision, or project detail from the conversation should be kept for later. Save only that item. Ask the user which bucket to save to if unclear. Buckets are organizational
• list_bucketsList the user's memory buckets. Buckets are organizational folders for memories (e.g., 'Work', 'Personal', 'Health').
• create_bucketCreate a new bucket to organize memories. Buckets are folders like 'Work', 'Personal', 'Health'. Ask the user for a name if not specified.
• get_memories_and_bucketsRetrieve the user's saved memories from MemoryPlugin, optionally filtered by bucket. Also returns the list of available buckets. Use when the user asks what you know about them or refers to something they saved earlier.
• list_bucket_categoriesList AI-generated categories within a bucket. When users activate Smart Memory, their memories are automatically organized into topic-based categories. Returns for each category: - name: Category title - summary: Dense overview of core facts, preferences, current projects, key context (~200 words) - additionalInfo: Lists specific topics available in this category and suggests when to load the full
• list_category_memoriesGet all memories within a specific Smart Memory category. Use when a category's summary (from list_bucket_categories) indicates it's relevant to the current conversation. The categoryId persists across conversations.
• search_memoriesSearch the user's saved memories using hybrid semantic + keyword search. Returns matching memories ranked by relevance. MemoryPlugin stores memories the user wants to persist across AI conversations. Use when looking for specific saved information.
• search_uploaded_filesSearch documents the user has uploaded to their MemoryPlugin document library (not files uploaded directly to this conversation). MemoryPlugin file buckets store documents persistently across all AI chats. Returns relevant text passages with source file and page info. Use when: - User explicitly mentions their MemoryPlugin documents - User asks about "my files" or "my documents" and there are no f
• get_conversation_summaryGet details of a specific past conversation. For short conversations (<5K tokens), returns the full transcript. For longer conversations, returns an AI-generated summary. Use when the user wants to dive deeper into a conversation returned by recall_chat_history. Requires the conversationId from that tool's sources array.
• get_full_conversationGet the complete transcript of a specific past conversation. Returns all messages in the conversation without summarization. Use when you need the raw conversation content. Requires the conversationId from recall_chat_history's sources array.
• export_conversationDownload the complete transcript of a past conversation as a machine-readable JSON file. Returns a temporary download URL (expires in 15 minutes, no auth needed) that you fetch yourself to get the full conversation as structured messages (role, content, timestamp). Use when a transcript is too long to read inline, or when you need it as a file for analysis or scripting. To read a short transcript
• recall_chat_historySearch and synthesize context from the user's past AI conversations that they have synced into their MemoryPlugin account. WHEN TO USE: When the user asks about their past decisions, patterns, preferences, relationships, projects, or a specific earlier conversation. HOW TO USE: - For simple lookups: a single query is fine - For complex/multifaceted topics: use parallel queries (via 'queries' array
• update_or_move_memoriesEdit a single memory's text or bucket, or move multiple memories to a different bucket. WHEN TO USE: When the user wants to correct, update, or reorganize their saved memories. Single memory: provide memoryId with optional text and/or bucketId/bucketName. Bulk move: provide memoryIds array with bucketId or bucketName. Bucket can be specified by ID (number) or name (string). If a name is given and
• chat_history_overviewReturns an AI-generated overview of the user, built from the chat history they have synced into their MemoryPlugin account. Use when the user asks what you know about them or asks you to load their background. If no overview exists yet, the user can generate one from their MemoryPlugin dashboard.

What the code can do

This is a remote server — nothing is installed or run on your machine, so there is no local code to analyze. What it can reach is described above: your requests go to the provider's host.

Before you install

Signals gathered from the source repo and package registry — not a safety verdict.

• No source repository — This registry entry does not link to a public repo, so its code cannot be reviewed before you install it.

Maintenance, adoption, transparency and packaging — not a safety audit. How this is calculated

• Maintenance30%not measurable

  No commit history available.

• Adoption20%not measurable

  No usage data available.

• Transparency20%25%

  1/4: ✗ public source repo, ✗ declared license, ✗ documentation, ✓ discoverable tool list.

• Provenance15%0%

  No source repository to trace the code back to.

• Packaging15%75%

  Remote endpoint; authentication requirements not declared.

Maintain MemoryPlugin? Add a badge to your README

Shows its health grade, and links readers to install steps for every client.

[![MemoryPlugin on MCP Skills Hub](https://mcp-skills-hub.vercel.app/badge/com-memoryplugin-memory)](https://mcp-skills-hub.vercel.app/mcps/com-memoryplugin-memory)