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    The open-source, self-organizing memory for all your AI tools. Persistent memory over MCP (remember, recall, observe): background agents extract entities, resolve conflicts, and keep cited syntheses current in an append-only, encrypted, single-tenant vault.
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    AGPL 3.0
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    Lets AI assistants understand what you're working on — current screen content, recent dictation, clipboard, and saved notes — running entirely on your own machine with nothing sent to the cloud.
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    AGPL 3.0
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    MCP server for the full Pāli Tipiṭaka — ~444,000 segments at parity with SuttaCentral (Sutta + Vinaya + Abhidhamma). Hybrid search, full-sutta fetch with cross-references, segment-aligned translation comparison, and Pāli word lookup. Offered as Dhamma Dāna.
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    MIT
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    Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.
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    Memory Consolidation for AI agents across vendors, owners, and time. Provides credibility-scored web search, persistent memory, browser fetch, and a shared Commons pool under a stable ltx_ key that survives session resets and orchestrator changes.
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    MIT
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    A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.
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    Apache 2.0
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    An MCP server that enables interaction with Markdown knowledge bases, allowing users to search and retrieve content by tags, text, URL, or date range from their local markdown files.
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    An MCP server that enables users to visualize Supermemory document data as an interactive memory graph within MCP-compatible clients like Claude. It provides a dedicated tool to fetch and render data as an interactive widget while keeping API keys secure on the server side.
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    MIT
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    Read-only MCP bridge that exposes secure search and fetch tools over an Obsidian-compatible Markdown vault, enabling ChatGPT to query notes without write access.
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    Apache 2.0
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    Provides persistent, anchored memory for AI coding agents, binding every decision to specific lines of code and delivering relevant context just-in-time via the Model Context Protocol.
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    MIT
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    Preserves the emotional texture of human-AI conversations across sessions through real-time experiential annotation — temperature, authenticity, shifts, subtext, and unspoken context.
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    MIT
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    Manages a research paper library, providing PDF ingestion, bibliography management, semantic search, figure tracking, and integration with Semantic Scholar.
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    AGPL 3.0
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    MindBase implements Karpathy's "LLM wiki" pattern as an MCP server. Instead of retrieving chunks at query time (RAG), the LLM maintains a persistent wiki between your conversations: it reads every source you feed it, cross-references pages with [[wikilinks]], flags contradictions between sources, and keeps a context.md that reflects your current synthesized thinking.
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    MIT