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

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    The official Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis.
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    MIT
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    Enables AI agents to manage and search data in Redis using natural language. Supports hashes, lists, sets, sorted sets, streams, JSON, and vector search.
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    MIT
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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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    FastMCP server with read-only tools to monitor Redis — queue depths, Celery queue status, connected clients, server/memory info, and per-database key counts
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    MIT
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    Enables AI to safely view and operate Redis databases with read-only mode by default and support for key operations.
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    MIT
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    Single MCP server that manages multiple personal collections (todos, bookmarks, etc.) with only six generic tools, driven by a YAML registry for validation.
    MIT
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    A server that provides Claude with Redis database access and operations through a set of tools for basic operations, lists, hashes, sets, and pub/sub functionality.
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    MIT
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    HandaaS的MCP服务器,提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力,帮助用户开展行业研究和舆情分析。
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    An MCP server that scans code repositories for app store rejection risks by mapping API usage to required declarations and policy deadlines, enabling agents to catch issues before submission.
    5
    MIT
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    Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.
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    MIT
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    Provides access to 21+ AI search parsers including Perplexity, ChatGPT, Claude, Gemini, Copilot, Grok, DeepSeek, and traditional search engines through the Redis API, enabling multi-source AI-powered search and information retrieval.
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    Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.
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    MIT
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    A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep
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    MIT
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    An MCP server providing long-term memory for LLMs via hybrid search (FTS5 + vector) stored in SQLite, with time-decay scoring and support for multiple AI assistants.
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    MIT