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    Provides emergency coding assistance by querying three AI coding models simultaneously through OpenRouter, with automatic premium fallback on rate limits, returning multiple expert opinions with cost and latency telemetry for debugging and problem-solving.
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    MIT
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    A comprehensive MCP server for automated bug bounty hunting and security reconnaissance, featuring over 28 specialized tools for subdomain discovery, vulnerability scanning, and traffic analysis. It integrates automated scope validation and professional reporting across multiple platforms like HackerOne and Bugcrowd to streamline security testing.
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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.
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    Apache 2.0
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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.
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    Bug-report triage and fix-dispatch MCP for vibe coders. Ask your AI coding agent for a plain-English diagnosis of any user-reported bug — with evidence, blast radius, and a paste-ready fix prompt — then dispatch an automated GitHub fix PR without a second LLM key. 71 tools, Supabase-backed, MIT SDK. npx @mushi-mushi/mcp
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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.
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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.
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    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.
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    MIT
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    An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.
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    MIT
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    Provides human-like memory dynamics for AI assistants where memories naturally fade over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve. Enables automatic saving, searching, and management of contextual information with temporal decay algorithms.
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    AGPL 3.0
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    Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.
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    Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.
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    MIT
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    Enables AI assistants to interact with Google's Jules coding agent API for autonomous coding tasks, allowing users to delegate bug fixes, refactoring, testing, and feature development with scheduling capabilities and human-in-the-loop approval workflows.
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