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    Provides an incident-centric knowledge graph via MCP stdio, enabling storage and query of incidents, systems, signatures, and their causal relationships, with tools for creating, linking, and tracing incidents.
    MIT
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    A Model Context Protocol server for Dify that provides culture-related services including courses, activities, user management, and search functionality.
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    Enables AI-driven job application automation for LinkedIn and SEEK platforms with intelligent cover letter generation, automated application submission, and application tracking management. Supports anti-detection measures and complies with platform usage policies for safe job hunting automation.
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    3
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    Apache 2.0
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    MCP server for searching and querying detailed housing listings in Taiwan, enabling AI to find properties with filters like city, district, room count, price, and age.
    2
    MIT
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    An MCP server that enables local AI models to receive guidance from remote 'senior' AI providers like OpenAI, Anthropic, and Gemini to solve programming problems. It features intelligent multi-turn dialogue management, context synchronization, and automated session history tracking.
    4
    11
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    Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.
    3
    MIT
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    Provider-agnostic email MCP server that connects any IMAP mailbox to AI assistants, enabling email management through natural language.
    8
    AGPL 3.0
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    A Bilibili MCP Server that can retrieve subtitles, danmaku (bullet comments), and comments information from videos using the video URL.
    3
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    MIT
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    Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.
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