"Redis" matching MCP servers:

Enterprise support ticket system using FastMCP server with Redis for persistent state and multiple clients.

A drop-in replacement for mcp-memory-duckdb with full concurrent access support using Redis Stack. Enables persistent knowledge graph storage with full-text search and multi-session concurrent access.

An intelligent memory MCP server that provides AI applications with semantic search, entity extraction, and knowledge graph capabilities using local Redis caching and optional cloud sync. It enables LLMs to store and retrieve long-term context across sessions with high-performance multi-tier storage.

Overcomes Claude Code's 200k token context limit by implementing persistent long-term memory using Redis and AI-powered state summarization. Enables seamless checkpoint and resume of project context across sessions.

Persistent memory for AI agents through the Model Context Protocol. MemStack provides tools to store, retrieve, summarize, prune, export, and manage memories using local files, SQLite, Postgres, Redis, or in-memory storage.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Provides MCP agents with persistent memory operations (store, recall, forget, consolidate, list) backed by Redis, Postgres, and pgvector, including semantic search and background consolidation.

A production-ready MCP server for persistent AI memory across LLMs like Claude and ChatGPT. Provides automatic conversation backup, multi-user support, and multi-storage (PostgreSQL, Redis, Qdrant).

Enables coding agents to write and recall long-term memories through a local, MCP-ready pipeline that extracts six memory categories on write and dispatches them by category view on read. Supports external OpenAI-compatible LLM endpoints and local Neo4j/Qdrant/Redis storage.

Enables querying course information, structured skills, and MCP knowledge with Redis caching, plus includes performance load testing capabilities.

An MCP server that transforms natural language questions into SQL, executes queries on PostgreSQL, and returns human-friendly responses, with Redis memory for context.