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    MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.
    4
    278 npm
    7
    Apache 2.0
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    Provides a local-first, provenance-aware memory layer that enables MCP-capable AIs to store, recall, validate, and reason over facts with contradiction detection, trust weighting, deduplication, and encryption, supporting offline private operation without GPUs or API keys.
    9
    Apache 2.0
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    Provides a read-only MCP interface to the Santismm Knowledge Platform, offering tools to retrieve curated content on engineering, AI patterns, architectures, governance, and agent taxonomy with structured output in English, Spanish, and Portuguese.
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    21 npm
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    MIT
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    Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.
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    MIT
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    A personal digital twin MCP server that manages professional context, including skills, experience, and project learnings. It allows AI assistants to retrieve and update user preferences and career interests across different development environments.
    4
    MIT
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    A server that enables AI agents to perform sophisticated knowledge discovery and analysis across Obsidian vaults through the Local REST API plugin, supporting complex multi-step workflows with advanced filtering and full content retrieval.
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    21
    MIT
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    Enables AI agents to use Obsidian vaults as persistent, bidirectional knowledge workspaces with wikilink/backlink resolution, structured frontmatter/tag indexing, task aggregation, and Obsidian Headless Sync.
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    MIT
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    An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.
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    Shared fleet memory for AI agents — what one agent learns, the whole fleet knows. Nightly self-correction: stale facts rewritten in place, duplicates merged. Recall pushed into every prompt in supported coding agents. Self-hosted.
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    MCP server that enables AI assistants to interact with the MemOS API, providing memory search, feedback management, and knowledge base operations via MCP-compliant tools.
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    Apache 2.0
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    Unofficial Notion MCP server built on Notion's private API (token_v2 cookie). Gives LLM agents full read/write access to the entire workspace — no integration token and no per-page sharing.
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    12 npm
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    MIT
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    A Model Context Protocol server that provides persistent memory capabilities for AI systems, enabling true continuity of consciousness across conversations through episodic, semantic, procedural, and strategic memory types.
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    MIT
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    AI development assistant with 36 specialized tools for memory management, code analysis, project planning, and problem-solving through natural language interactions in Korean and English.
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    3
    MIT
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    A structured project memory MCP server that persists plans, builds, reviews, and decisions across AI coding sessions and tools, enabling continuous project management with a dashboard.
    11
    MIT
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    Gives MCP clients a small remote Streamable HTTP tool surface for a Brain memory database, letting agents store facts, retrieve current-truth answers with evidence, delete memories, and check their effective identity. Each call is scoped by a customer identifier for per-customer isolation, and the endpoint can optionally be secured as an OAuth 2.1 resource server.
    561 npm
    1
    Apache 2.0
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    Enables AI assistants to read, search, and write Markdown notes kept in Postgres, alongside a web app with a file tree, wikilinks, full-text search, and a graph. Supports OAuth or API-key connections, per-account vaults, and folders shared with other people read-only or read-write.
    AGPL 3.0
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    Enables AI assistants to search, create, and manage knowledge graphs in Aiqbee brains for architecture, portfolio, and digital strategy.
    7
    MIT
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    MCP server for the Crosmos memory layer, enabling semantic, keyword, and graph retrieval of memories, as well as storing content with automatic entity and relation extraction.
    15 npm
    2
    MIT
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    Provides LLM clients with persistent memory tools for searching, reading, creating, and updating notes, retrieving backlinks, listing recent notes, and managing tasks using self-hosted MySQL storage.
    43 npm
    MIT
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    Open-source AI memory layer for LLM agents. Importance scoring, temporal decay, hierarchical memory (facts, summaries, themes), YMYL prioritization, and active retrieval with contradiction detection. Supports OpenAI, Anthropic, Ollama. Local-first with SQLite + FAISS.
    28 PyPI
    48
    Apache 2.0
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    An MCP server that tracks AI prompts in Claude Code and automatically annotates git commits with the history of what was asked. It provides tools to query session summaries, retrieve uncommitted work, and manage AI provenance directly within Claude.
    AGPL 3.0
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    Enables AI agents to perform fused hybrid search and reorganize documents, folders, and metadata in the SAGA document archive via MCP tools.
    1
    Apache 2.0
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    Provides durable project context for coding agents, including project maps, session history, and explicit memories, all stored locally.
    43 npm
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    MIT