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    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
    11
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    A local MCP server that helps you maintain a personal Japanese learning knowledge base, including vocabulary, confusion relations, mistakes, and spaced-repetition reviews. It provides tools and prompts for managing and reviewing your Japanese learning data without calling external LLM APIs.
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    Search and retrieve news articles and trending keywords from Google News and Google Trends. Summarize articles and extract keywords using optional NLP and LLM Sampling to get concise insights.
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    MIT
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    A cross-AI-agent local task context sharing MCP server that allows clients like Codex, Claude Code, Hermes, and VS Code to read and write the same task state, enabling task tracking and context distillation.
    6
    MIT
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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.
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    MIT
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    MCP server for AI agents providing 300 curated Japanese home & lifestyle products across 31 categories. Features mm-precision dimension search, related-item chains (1 product → 3-5 accessories), shelf+storage coordination, and Rakuten/Amazon affiliate links.
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    A multi-domain MCP server that exposes a small, stable surface of three tools (list_domains, list_domain_tools, call_domain_tool) to gate access to various tool domains like Plane and BloodBank, preventing agent schema overload.
    3
    MIT
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    A unified MCP server that aggregates 32 sports API providers into a single service, providing 336 tools for scores, stats, odds, esports, and more across 70+ sports.
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    MIT
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    Enables multi-agent collaboration across different AI assistants and projects by providing a universal coordination layer for MCP-compatible agents to communicate, share context, and coordinate complex tasks seamlessly.
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    Aggregates game-development MCP servers (Blender, Godot, GitHub, Obsidian) behind one interface for AI clients, with smart task routing and a local GUI for multi-client support.
    5
    MIT