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    Provides read-only Arknights intelligence over MCP, enabling structured queries about stages, enemies, operators, and modules with region tagging and evidence-backed analysis. It uses versioned SQLite snapshots and never fetches upstream data at query time.
    4
    13
    Apache 2.0
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    Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.
    26
    23
    Apache 2.0
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    Equips AI coding agents with 62 production-grade tools across 28 modules for persistent memory, live GitHub scouting, UI/UX design, DevOps, security, performance auditing, and SEO/AEO/GEO optimization, enabling automated, development workflows.
    63
    1
    MIT
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    MCP server providing permanent, intelligent memory for AI coding assistants with retrieval, Hebbian learning, and governance, plus personal memory modules for accounts, habits, experiences, knowledge, and lifestyle. Enables AI assistants to recall project context across sessions and manage personal data securely.
    MIT
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    Enables AI assistants to read Lanhu design collaboration content: extracting and analyzing Axure prototype pages, downloading UI designs and slices, and converting design specs into HTML+CSS for implementation. It also provides a shared team message board so multiple AI tools can reuse requirement analyses and knowledge across projects.
    MIT
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    Living typed knowledge graph for software projects, exposed over MCP so coding assistants can capture and query modules, capabilities, flows, events, rules and decisions across sessions. SQLite-backed, schema-validated, ships as a Claude Code plugin.
    MIT
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    Enables SDD artifacts — concepts and immutable revisions of problems, research, specifications, designs, tasks, ADRs, and roadmaps — to be saved, listed, and retrieved in a CouchDB instance you run yourself. It serves the artifact tools that sddv3 skills call, exposing them over a Streamable HTTP MCP endpoint without authentication.
    MIT
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    Exposes codebase memory as native tools for AI agents, enabling queries, feature tracing, impact analysis, and alignment verification.
    5
    AGPL 3.0
  • A
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    Anchors a codebase's engineering context — file cards, rules, modules and decisions — in a small git-committed graph, and injects the applicable slice before each edit while refusing changes to files the agent hasn't actually understood. It also records the why behind each constrained edit so later sessions and teammates start from that understanding instead of rediscovering it.
    1,317 npm
    MIT
  • A
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    Bridges MCP to a self-hosted Mem0 OSS server, enabling memory management operations like adding, searching, updating, and deleting memories.
    MIT
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    An MCP server that enables a private mobile-first reading experience in ChatGPT, managing multi-book shelves, reading progress, highlights, thoughts, and bookmarks, with secure cloud storage and AI co-reading of the current page.
    27
    MIT
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    Enables natural-language control of CST Studio Suite for electromagnetic simulation, covering modeling, materials, ports, solvers, result reading, and VBA scripting, with an embedded knowledge base and constraint hooks that self-evolve through use.
    8
    Apache 2.0
  • F
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    Not graded
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    Enables coding agents to query a local-first code intelligence graph of Python repositories—covering functions, classes, modules, and their relationships—via MCP, supporting subgraph retrieval, caller lookup, and impact analysis without re-reading the codebase.
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  • F
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    maintenance
    MCP server that implements a cognitive survey response framework by storing persona information in a modular database and allowing LLMs to selectively retrieve relevant modules for each survey question.
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  • A
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    Provides a memory server for coding agents over MCP, capturing and retrieving the meaning and rationale behind code decisions down to the function level. It enables agents to search product memory, get task context, and propose new memories to avoid re-deriving or re-breaking past decisions.
    9
    MIT