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    Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.
    8
    MIT
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    Exposes NVIDIA GPU metrics (info, utilization, VRAM, temperature) via MCP tools for real-time querying from AI assistants.
    5
    MIT
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    MCP server that vets LLM-emitted shell commands BEFORE execution — detects rm -rf nested deep in chains, package-manager glob removal (apt remove 'nvidia'), dd/mkfs filesystem destruction, chmod 777 / chown -R privilege blast, network-exfil via curl | bash, chained shutdown/reboot, git destructive ops. 30 detection rules across 8 families. Sub-second, local, free, MCP-native.
    3
    MIT
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    VibOps MCP is the control plane between your AI agents and your GPU infrastructure. 74 tools covering: GPU fleet management (deploy, scale, monitor across NVIDIA, AMD, Intel, AWS, Google, Groq), Agent Infrastructure Control Plane (per-agent GPU cost, budget enforcement, model policies, dependency graph), governance (AI Act, SOC 2, immutable HMAC audit chain), and GPU FinOps (chargeback, waste..)..
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    MIT
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    Enables natural language control of NVIDIA Isaac Sim through the Model Context Protocol, allowing you to create robots, build scenes, run simulations, and debug physics from any MCP-compatible IDE.
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    51
    MIT
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    A local text-to-image generation server that enables AI agents to generate images, manage models, and browse history using the Z-Image-Turbo model. It supports hardware acceleration across NVIDIA, Apple Silicon, and AMD GPUs via multiple MCP transport protocols.
    3
    124
    Apache 2.0
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    Dual-memory MCP system with PostgreSQL 17 + pgvector + NVIDIA NIM embeddings. 11 tools: search, save, profile, health, auto-repair, stats, tune, dedup, checkpoint, maintenance. Sparse Selective Caching (SSC) with 4-phase progressive retrieval. Bilingual EN/ES.
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    MIT
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    A lightweight MCP server that provides real-time hardware statistics including CPU, memory, disk, and NVIDIA GPU usage. It enables users to monitor system performance and retrieve comprehensive host machine specifications through a standardized interface.
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