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"Design Architecture of Ontology-based AI-PHM Using Life Acceleration Algorithms" matching MCP servers:

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    Enables AI assistants to navigate and populate complex ontologies by transforming unstructured data into structured, SHACL-validated knowledge graphs. It features semantic hybrid search and proactive schema guidance to help users build deeply linked, reasoning-ready data.
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    Provides source-backed design context, route card validation, contract generation, critique and verification reports, evidence packages, Penpot change plans, and anti-repeat checks for design workflows. Does not directly mutate Penpot, but consumes read-only Penpot snapshots.
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    MIT
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    Enables AI assistants to search, create, and manage knowledge graphs in Aiqbee brains for architecture, portfolio, and digital strategy.
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    MIT
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    Design contract layer for AI agents. Scans Figma, code, Storybook, and token files, reconciles conflicts, and serves a single machine-readable source of truth so every agent gets the same authoritative design rules before it builds. Local-first.
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    6
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    Apache 2.0
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    An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.
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    5
    Apache 2.0
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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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    8
    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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    A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.
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    5
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    Apache 2.0
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    A productivity coaching assistant designed for ADHD support that provides intelligent task management, goal tracking, and personalized recommendations. It utilizes a persistent memory system to learn user patterns and preferences, helping to reduce decision paralysis through actionable suggestions.
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    Personal multi-LLM memory repository using Markdown as source of truth, SQLite FTS5 for retrieval, and MCP tools for search, context, and write proposals.
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    Apache 2.0
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    AoT MCP server enables AI models to solve complex reasoning problems by decomposing them into independent, reusable atomic units of thought, featuring a powerful decomposition-contraction mechanism that allows for deep exploration of problem spaces while maintaining high confidence in conclusions.
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    MIT
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    Enables AI-powered knowledge management and creative support by connecting Scrapbox data to Claude. Supports advanced search, relationship analysis between pages, theme extraction, and literary analysis of personal knowledge bases.
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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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    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.
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    49
    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.
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    AGPL 3.0