mem0-local-mcp
Related Servers
Alternatives to mem0-local-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceProvides persistent semantic memory for AI agents via MCP, enabling them to remember, recall, list, update, and forget memories with vector-based similarity search.ISC
- AlicenseNot gradedqualityAmaintenanceProvides persistent memory for AI coding agents via MCP, enabling agents to store and semantically recall facts, events, and lessons across sessions, all running locally without cloud dependencies.Apache 2.0
- AlicenseAqualityDmaintenanceProvides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.41MIT
- AlicenseAqualityBmaintenanceProvides persistent, searchable memory for AI agents across any MCP-compatible client, storing project context, user preferences, and session learnings locally in SQLite with tools to save, retrieve, search, and manage them.127 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
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to store, retrieve, and manage persistent memories locally via an MCP server with hybrid vector and keyword search, plus tools for memory CRUD, search, backup, and import.MIT
TDQS
Scored across 3 tools
The three tools map to clearly distinct operations: add_memory (create), search_memory (read/query), and delete_memory (remove). Descriptions reinforce the boundaries, e.g. add_memory explicitly tells the agent to search first, eliminating overlap.
All three tools follow the identical verb_noun pattern (add_memory, search_memory, delete_memory) with the same noun for the resource. This is a textbook consistent naming scheme.
Three tools is a tight, well-scoped surface for a simple local long-term memory store. Each tool earns its place with no redundancy or filler.
Create, query, and delete cover the core memory lifecycle, and semantic search serves as retrieval. An explicit update/edit tool and a get-by-id or list operation are missing, though delete+add can work around the gap.