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"Self-hosted MCP server on Proxmox LXC container accessible from AI on a separate PC" matching MCP servers:

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    A self-hosted Model Context Protocol server for Microsoft To Do. The key problem this solves: the Microsoft Graph API silently omits user-created lists on personal accounts (GET /me/todo/lists only returns well-known lists like "Flagged Emails"). This server works around it with a local SQLite registry that tracks every list you create, so your lists always show up.
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    Comprehensive Discord selfbot MCP server enabling AI assistants to manage messages, channels, voice, friends, threads, and more using a user token.
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    MIT
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    Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.
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    An MCP server that enables AI assistants to control Blender through 108 specialized tools for 3D modeling, animation, and rendering. It provides a secure, thread-safe interface to execute validated operations in Blender using natural language commands.
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    AGPL 3.0
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    Enables AI assistants to present multiple UI component designs in a browser for visual selection, with AI-powered design generation using MiniMax-M2.1 from natural language prompts or manual HTML input.
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    MIT
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    Sends system notifications when AI completes responses in MCP-compatible code editors, with cross-platform support for macOS, Windows, and Linux including customizable titles, messages, icons, and sound effects.
    2
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    A text processing workbench and MCP server that provides 22 tools for cleaning, transforming, and extracting data from text. It enables AI assistants to perform complex operations like regex extraction, log normalization, and encoding through a unified interface.
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    MIT
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    Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.
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    Apache 2.0
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    Enables users to connect and run Stack AI workflows directly through MCP-compatible clients. It allows for passing user inputs to specific projects and receiving structured responses from deployed AI applications.
    1