Mem0 MCP

Mem0 is an AI memory layer that stores, retrieves, and updates user-specific context across sessions. Its MCP server lets any AI agent save important facts, preferences, and past conversation context to a persistent memory store, then recall them intelligently in future sessions. This solves the fundamental limitation of stateless LLMs — every session starts fresh — by giving agents access to a growing knowledge base of what it knows about the user, their projects, and their preferences. Supports hybrid vector + graph memory for both semantic and relational recall.

Mem0 MCP is a AI & LLM MCP server designed for AI engineers, researchers, and product teams. It enables orchestrating models, embeddings, and vector stores from an MCP client by normalising provider APIs into MCP tools for routing and composition. Key capabilities include multi-provider model access, embeddings and similarity search, vector store crud, and structured tool calls that work cleanly inside an LLM context. It integrates with OpenAI, Anthropic, Google, Mistral, Pinecone, Weaviate, Qdrant, and Chroma, and is best suited for AI engineers, researchers, and product teams who need multi-model routing.