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by KerolIA98 • Search & Retrieval
An MCP server template that integrates Mem0 to provide AI agents with persistent, searchable long-term memory.
Store and recall user-specific facts or context across conversations to maintain long-term personalization.
Semantically search past interactions and memories to provide relevant historical context during decision-making.
An MCP-compatible memory backend to integrate with MCP clients over SSE or stdio and leverage embeddings/vector search.
This repository implements a Model Context Protocol (MCP) server using Mem0 for semantic memory storage and retrieval. It provides tools to save memories, retrieve all memories, and perform semantic searches backed by a PostgreSQL/vector store. The project is a template demonstrating how to wire LLMs, embeddings, and a vector database into an MCP-compatible server for use with MCP clients (SSE or stdio). It is intended as a practical starting point for building custom MCP servers with persistent agent memory.
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