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"Information about Redis, an in-memory data structure store" matching MCP servers:

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    Enables AI assistants to perform comprehensive Redis database operations including managing strings, hashes, lists, sets, sorted sets, TTL management, and data backup/restore. Supports secure connections and provides batch operations for efficient Redis interaction through natural language.
    34
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    MIT
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    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.
    23
    MIT
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    Provides a shared memory bridge for AI agents (QClaw, Claude Code, Codex) allowing them to store, search, and retrieve notes, decisions, and conclusions via MCP tools, using local SQLite with optional TencentDB integration.
    MIT
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    A lightweight MCP server that records and reuses prompt gaps — essential context missing from initial instructions — so your AI assistant learns from every session using a plain JSONL file tracked by Git.
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    Provides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.
    15
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    7
    MIT
  • A
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    Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for your preferred MCP client. Inspired by and forked from @modelcontextprotocol/server-memory
    3
    MIT
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    An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.
    MIT
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    Enables AI agents to share persistent memory via an MCP server using SQLite, supporting multi-tenant, categorized knowledge with TTL and semantic links, without requiring vector databases.
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    Enables routing context and execution across AI tools like Claude, Cursor, Windsurf, and ChatGPT with a shared memory, task board, and context bus, plus local file conversion.
    10
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    Apache 2.0
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    This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Google Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=HGZK-V&type=beta
    MIT