Walrus Memory MCP
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Alternatives to Walrus Memory MCP
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AlicenseNot gradedqualityBmaintenanceEnables MCP clients to connect to a locally running memory layer for AI assistants, providing tools to remember, recall, forget, expand, and sync connectors.95 npmMIT- AlicenseNot gradedqualityAmaintenanceProvides a shared long-term memory across any LLM via MCP, enabling semantic recall, session save/reload, and multimedia memory management with local embeddings and private storage.MIT

Kova Mind MCP Serverofficial
AlicenseAqualityCmaintenanceEnables AI memory persistence and secure credential management via vault tools for MCP-compatible clients like Claude Desktop, Cursor, and VS Code.1211 npmMIT- AlicenseNot gradedqualityCmaintenanceEnables AI clients to read and write a single self-hosted memory store over MCP, so memories persist across models and sessions, with JSON import/export for portability.MIT

LedgerMem MCP Serverofficial
AlicenseNot gradedqualityBmaintenanceEnables persistent memory storage and retrieval for MCP clients, allowing AI assistants to remember facts and context across conversations.18 npmMIT- AlicenseNot gradedqualityNot gradedmaintenanceIntegrates the Mem0 Memory API with MCP-compatible clients to provide AI agents with persistent, long-term memory capabilities. It enables users to add, search, update, and delete memories to maintain context and personalization across different interactions.Apache 2.0
TDQS
Scored across 5 tools
Each tool serves a distinct purpose: login for authentication, remember for explicit saving, analyze for batch extraction, recall for searching, and restore for index maintenance. Although analyze and remember both create memories, their trigger conditions are clearly separated (passage processing vs. direct user request), preventing misselection.
All tools follow a uniform memwal_<verb> pattern using lowercase snake_case. The verb stems (analyze, restore, login, remember, recall) are consistent and predictable, making the naming highly coherent.
With only five tools, the surface is compact and focused on the essential operations of a personal memory system: authentication, writing, reading, batch processing, and maintenance. No tool feels redundant or extraneous.
The set covers authentication, creation, recall, and bulk ingestion, but lacks update and delete operations. For a memory system, the inability to forget or correct stored facts is a notable gap that could limit agent effectiveness.