"Search related to 'mem0'" matching MCP servers:

An MCP server that provides persistent memory capabilities for AI agents using Mem0, enabling storage, search, and management of contextual information across conversations with support for multiple backends and LLM providers.

Self-hosted Mem0 MCP server integrating Qdrant, Neo4j, and Ollama for semantic memory search, graph entity relationships, and memory management via OpenMemory API.

A server that wraps a self-hosted mem0 REST API as MCP tools for Claude Desktop and Claude Code, enabling memory operations such as adding, searching, and managing memories via natural language.

A local MCP server that exposes Mem0 as persistent memory tools to any MCP client, storing data locally with no cloud API or API key required.

Enables AI applications to add, search, update, and delete long-term memories using the Mem0 Memory API, allowing agents to persistently remember user preferences, conversation history, and contextual information across sessions.

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

An MCP server that integrates with mem0.ai to help users store, retrieve, and search coding preferences for more consistent programming practices.

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.

Provides long-term memory capabilities for MCP clients by wrapping the Mem0 API, enabling semantic search, storage, retrieval, and management of conversation memories across users and agents.

A custom MCP server that connects to self-hosted Mem0 API instances, enabling Claude Code to manage memories via custom endpoints.

Intercepts Claude conversations via MITM proxy and stores them in Mem0, enabling Claude to search and recall past conversations, learn user preferences, and maintain context across sessions.

Enables AI agents to store and retrieve memories with user-specific context using Mem0, allowing them to maintain conversation history and make informed decisions based on past interactions.

Provides AI agents with persistent long-term memory capabilities using semantic search. Enables storing, retrieving, and searching memories through three core tools integrated with Mem0 and vector storage.

A Model Context Protocol server that integrates AI assistants with Mem0.ai's persistent memory system, allowing models to store, retrieve, search, and manage different types of memories.

A TypeScript implementation of the Model Context Protocol server that enables creation, management, and semantic search of memory streams with Mem0 integration.

Enables MCP clients like Codex, Cursor, and Claude Code to use memory tools backed by a self-hosted Mem0 OSS instance via a Streamable HTTP adapter.

MCP protocol server exposing Mem0 AsyncMemory API for AI agent context retention

Enables memory storage and retrieval using Mem0, allowing users to store context-specific memories and search through them with relevance scoring.

Bridges MCP to a self-hosted Mem0 OSS server, enabling memory management operations like adding, searching, updating, and deleting memories.

MCP server wrapping a self-hosted mem0 REST API, enabling memory management with deduplication and mention-aware reranked search.

A thin stdio MCP bridge to a self-hosted mem0 OSS server for agent memory, enabling persistent memory operations like adding, searching, and managing durable facts with automatic reconciliation and question-rewrite capabilities.

A Model Context Protocol server that provides AI agents with persistent memory capabilities through Mem0, allowing them to store, retrieve, and semantically search memories.

A template implementation of the Model Context Protocol server that integrates with Mem0 to provide AI agents with persistent memory capabilities for storing, retrieving, and searching memories using semantic search.

A robust server for managing long-term agent memory using Mem0, providing efficient storage and retrieval of agent memories with a lightweight Python-based implementation.

Open-source MCP server for mem0 that enables memory storage and retrieval using local LLMs, self-hosted, and Docker-free.

A local Mem0 memory system integrated with Anthropic Claude via MCP, enabling persistent memory for AI interactions with vector and graph storage.

A remote MCP server deployed on Cloudflare Workers for memory storage and retrieval using Mem0, supporting SSE and standard MCP connections.

An MCP server for mem0 memory management backed by Qdrant, with per-collection isolation via HTTP headers. Enables storing, searching, updating, and deleting memories through natural language.

Enables storing and searching memories via Mem0 API directly from Cursor, allowing natural language interaction with persistent memory.

Enables persistent storage and semantic search of coding preferences, patterns, and implementations using Mem0, allowing AI agents to remember and retrieve development best practices across sessions.