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    The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug
    2
    MIT
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    MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.
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    Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.
    25
    92 PyPI
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    MIT
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    A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.
    11
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    Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.
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    AGPL 3.0
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    An MCP server that enables AI agents to execute Lua code, inspect scripts, spy on remotes, and interact with running Roblox game clients, including support for mobile executors on Android and iOS.
    58 npm
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    MIT
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    Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.
    6 npm
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    MIT
  • -
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    A platform that transforms AI development with intelligent context management, optimization, and prompt engineering, enabling developers to enhance model performance through structured context management and optimization tools.
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    This MCP server integrates AI assistants with Unity Editor, allowing them to create scenes, generate scripts, simulate input, and automate workflows using 91 built-in tools.
    265
    MIT
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    Turns any LLM into a coding co-pilot with production-ready MCP server providing lint, test, execution, generation, and graph tools. Features Neo4j persistence, OpenAI Agent integration, REST API, and React frontend for comprehensive code development assistance.
    MIT