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    Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.
    6
    MIT
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    TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.
    2
    Apache 2.0
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    Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.
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    MIT
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    Enables seamless integration between Claude and Dry smartspaces, turning conversations into persistent, structured data by creating memories and querying information.
    7
    MIT
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    File-backed Memory MCP Server for multi-agent coordination, enabling AI coding agents to persistently store and search memories using JSON files without external services.
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    MIT
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    Provides persistent, searchable memory for Claude Code using local SQLite, semantic embeddings, and full-text search, enabling Claude to recall and retrieve context across sessions and projects without external services.
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    3
    MIT
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    A persistent memory layer for AI tools that decouples personal data from AI's unstable memory, enabling you to mention information once and have it remembered forever across all conversations.
    3
    MIT
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    Enterprise MCP server that exposes multiple MySQL databases to AI services through one endpoint, with API-key auth, per-key database scoping, a layered SQL guard, and a markdown schema-knowledge graph.
    70
    MIT
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    An MCP server that gives AI assistants the ability to remember user information (preferences, behaviors) across conversations using vector search technology.
    15
    MIT
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    Enables storing and retrieving information using semantic search with Qdrant vector database. Acts as a memory layer for LLMs to persistently store and semantically search through information and metadata.
    Apache 2.0
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    Exposes Colber's five integrated services (Reputation, Memory, Observability, Negotiation, Insurance) as 27 MCP tools for AI agents, enabling trust, coordination, and continuity.
    Apache 2.0
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    A local memory server for AI agents that stores and retrieves information via MCP, keeping all data in SQLite on your machine.
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    Apache 2.0
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    Enables MCP clients like Cursor and Claude to remember user preferences and information across conversations using vector search.
    15
    MIT
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    Enables large language models to directly access and search content in ZIM files, allowing offline question answering and information retrieval from resources like Wikipedia.
    19
    MIT
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    Intelligent context-aware memory system for AI assistants that enables persistent memory, automatic development activity tracking, and intelligent information retrieval across conversations.
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    MIT