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"Enhancing Claude-based Code Generation" matching MCP servers:

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    A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.
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    MIT
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    Read-only MCP server to list your SkyNode servers and check their status (IP, state, region, expiry). It does not modify or control servers.
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    MIT
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    Enables AI-powered creation, configuration, and management of DevContainer environments using natural language prompts. Supports 11+ templates for popular development stacks and provides container lifecycle operations through VS Code, Cursor, or any MCP-compatible editor.
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    MIT
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    Enables running arbitrary JavaScript code in isolated Docker containers with on-the-fly npm dependency installation, supporting both ephemeral one-shot executions and persistent sandbox environments.
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    Provides unified control for both physical robots (ROS-based like Moorebot Scout, Unitree) and virtual robots in Unity3D/VRChat, enabling multi-robot coordination, environment generation, and automated 3D model creation.
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    MIT
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    Facilitates isolated code execution within Docker containers, enabling secure multi-language script execution and integration with language models like Claude via the Model Context Protocol.
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    MIT
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    GenieACS-MCP is a Go-based MCP server that bridges any GenieACS (TR-069 ACS) instance, exposing device data, firmware management, and CPE actions (reboot, parameter refresh, firmware download) over JSON-RPC
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    GPL 3.0
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    Read-only VMware vCenter/ESXi monitoring. 8 MCP tools for VM inventory, host status, datastore capacity, cluster info, alarms, events, and VM details. Code-level enforced safety — no destructive operations exist in the codebase. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.
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    MIT
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    Connects Claude Desktop to any Kubernetes cluster, enabling natural language queries for diagnostics and operations such as listing pods, viewing logs, scaling deployments, and more.
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    Enables AI agents to interact with Kubernetes clusters through progressive disclosure, where agents discover TypeScript modules via filesystem, write and execute code, and receive summarized console output for cluster management tasks.
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    MIT