MCP server for long term agent memory with Mem0. Also useful as a template to get you started building your own MCP server with Python!

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✨ mem0 MCP Server: A memory system using mem0 for AI applications with model context protocl (MCP) integration. Enables long-term memory for AI agents as a drop-in MCP server.

Self-hosted mem0 MCP server for Claude Code. Run a complete memory server against self-hosted Qdrant + Neo4j + Ollama while using Claude as the main LLM.

Persistent memory for AI agents - Learn, remember, improve. Alternative to Mem0 with scoped learning, anti-patterns, multi-agent sharing, and MCP integration.

OpenAI just added memory across your chats across your openAI account. But wouldn't it be awesome to have general AI memory across all your interactions with any and all AI tools, IDEs, chatbots.... Now if it supports MCP you can with https://mem0.ai/ Give Claude desktop memory. Give cursor or windsurf memory across sessions or different projects.

MemVault 自托管的 AI 记忆管理平台 — 为 AI Agent 提供持久化的跨会话记忆能力。 基于 mem0 构建，提供完整的多租户管理界面、RESTful API、MCP 协议支持和 OpenClaw 插件，让你的 AI Agent 真正"记住"每一位用户。

mem0项目的mcp服务优化：添加了类openAI接口的LLM和Embedding模型支持

MCP-Mem0-docker: Long-Term Memory for AI Agents based on mem0.ai

🧠 Production-ready MCP server providing intelligent memory for Claude Code with async architecture, Neo4j knowledge graphs, smart chunking & enterprise security. One-command Docker deployment.

All-in-one AI chat studio — 7 providers (Ollama, Claude, OpenAI, vLLM, Claude Code, Codex, Gemini CLI), RAG knowledge base, MCP tool integration, Mem0 shared memory, and 3-step pipeline. 100% local-capable. MIT licensed.

MCP-Mem0: AI智能体的长期记忆 - 一个集成了Mem0的模型上下文协议(MCP)服务器

AI Agent Fleet Memory System — Qdrant + Mem0 + Neo4j/Graphiti. Composite scoring, compaction engine, temporal knowledge graph, multi-claw federation, sleep-time reflection, MCP server.

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MCP server for self-hosted Mem0 with Qdrant vector + Neo4j graph memory

Agentic BI SaaS platform for natural language analytics using LangGraph, LangChain, LLMs (OpenAI, LLaMA, Mixtral), RAG with FAISS/Chroma, SQL & BI agents, MCP tools, and long-term AI memory (mem0). Built with FastAPI, Streamlit, Plotly, SQLAlchemy, PostgreSQL,Docker,Kubernetes,governance, lineage, RBAC,usage-based billing,SaaS & on-prem deployment.

A quick self hosted mem0 mcp server

Production-grade multi-agent SRE platform using LangGraph, MCP, and A2A protocols. 5 autonomous agents (Monitor, Diagnose, Policy, Remediate, Report) with episodic memory (Mem0), AI governance guardrails, human-in-the-loop approval gates, and 87% cost optimization via intelligent model routing.

Next-generation agent memory persistence combining three separate current state of the art memory technologies into a coherent system orchestrated by an MCP server. (i.e. mem0 + memgraph + RAG-based grounding + mcp server orchestration)

local-ltm is a local Model Context Protocol (MCP) server that provides long-term memory for AI agents. It allows a single user to run multiple AI agents that can store, search, update, and delete durable memory (preferences, facts, skills) using mem0 as the memory backend.

Memory for AI Agents; SOTA in AI Agent Memory; Announcing OpenMemory MCP - local and secure memory management.

glassBead's custom MCP server for mem0

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Production-ready Model Context Protocol server for comprehensive agent memory management with Docker deployment, multi-database architecture, and GitHub OAuth authentication

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Self-hosted MCP Server for AI memory with PostgreSQL (pgvector).

Host a complete memory server using mem0 with Qdrant, Neo4j, and Ollama for powerful memory management and LLM integration with Claude or Ollama.

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Mem0 memory system with Anthropic Claude API and MCP integration

Cloudflare Workers 远程 MCP 模板，集成 Mem0 记忆工具；Cloudflare Workers remote MCP template with Mem0 memory tools.