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    Enables AI tools to analyze Java dependencies by scanning Maven projects, decompiling JAR files, and extracting detailed class information including methods, fields, and inheritance relationships. Solves the problem of AI hallucinations when generating code that calls external dependencies by providing accurate class structures through decompilation.
    3
    27
    42
    Apache 2.0
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    A tool for detecting and cleaning Java memory shells via local or SSH remote execution. It enables AI agents to scan Java processes, analyze suspicious class code, and safely remove memory shells after user confirmation.
    9
    25
    MIT
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    Provides semantic code intelligence tools (search, structural views) and a workspace TUI interface for LLM agents to efficiently navigate codebases, manage context, and maintain architectural patterns across Python, Java, C++, and Perl projects.
    4
    MIT
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    Generates AI-powered clarifying questions for user task requests using Claude, helping gather detailed requirements about tech stack, architecture, deployment, and project scope through categorized, contextually relevant questions.
    MIT
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    Enables controlling an autonomous Minecraft Java Edition player through MCP, with structured world perception, navigation, gathering, crafting, combat, building, skill-based task execution, and long-term memory integration.
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    Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.
    4
    18
    MIT
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    Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.
    7
    24
    8
    Apache 2.0
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    Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.
    3
    9
    MIT
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    Enables LLM assistants like Claude to interact with Zaif cryptocurrency exchange through natural language, supporting market information retrieval, chart data, trading, and account management for BTC/JPY, ETH/JPY, and XYM/JPY pairs.
    9
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  • F
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    Enables AI assistants to play Pokemon Fire Red through the mGBA emulator by providing tools for button inputs and screenshots. It allows for direct reading of real-time game state from RAM, including party information, player location, and battle status.
    10
    3
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    MCP server for the FLOX trading framework. About 30 tools to run backtests, scaffold strategies, validate for lookahead bias, compute indicators, place orders, and query PnL from Claude/Cursor.
    38
    223
    MIT
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    Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.
    16
    11
    MIT