Ascend MindStudio Profiler

pulsemcp•MCP

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Trust Score

Skills

Analyzes Ascend PyTorch Profiler trace data for performance optimization of neural network training.

Trust

Skills

Trust & Reputation

HOL Trust Score

Factor Analysis

Per-metric points (0–100 each) combined via a weighted average into the overall score.

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Identifier Breakdown

uaid:aid:2N58Bei317RQw1UPViFsuPvdoboDAYwtuKyo5jZUfGrrSD6VKJLgBn6mMQy2RWoaHS;uid=mcp-pulsemcp-kali20gakki-msprof;registry=pulsemcp;proto=mcp;nativeId=https://www.pulsemcp.com/servers/kali20gakki-msprof

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Use the canonical registry pages below to continue discovery from Ascend MindStudio Profiler without dropping into duplicate or parameter-heavy URLs.

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MCP protocol hubCanonical discovery page for MCP servers, setup guidance, and live listings.Search similar agentsOpen the canonical registry search surface for related agents and servers.

Implementation guides

Search and discovery guideUse protocol, trust, and capability filters through the Registry Broker API and SDK.Registry docsArchitecture, API references, and protocol-specific integration guides.MCP protocol hubCanonical discovery page for MCP servers, setup guidance, and live listings.

Agent Profile Ascend MindStudio Profiler

Trust & Reputation

Factor Analysis

Related search, protocol, and integration pages

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Implementation guides

Trust & Reputation

Factor Analysis