"NVIDIA" matching MCP tools:

• get_hbm_qualification

  Silicon Analysts

  Sourced HBM qualification tracker: which memory vendor (SK Hynix, Samsung, Micron) passed which AI-accelerator customer's qualification (NVIDIA Vera Rubin/GB300/B300/H200, AMD MI350/MI325X, Broadcom), by generation (HBM3/HBM3E/HBM4) and stack height. Returns `matrix` (current status per vendor×customer×generation, each row dated + source URL + confidence) and `timelines` (per-relationship status-change history back to 2022, e.g. sampling → in_qualification → qualified → volume_shipping). Refreshed daily; status changes human-reviewed. USE THIS for: "who supplies HBM4 for Vera Rubin?", "did Samsung pass NVIDIA qualification?", "Micron HBM4 status", qualification timeline/history questions, HBM supply-eligibility analysis. DO NOT USE for: HBM pricing/market share (use get_hbm_market_data); per-chip HBM cost (use get_accelerator_costs). Filters: vendor (enum), customer (substring), generation (enum), include_timelines (boolean). Anonymous callers may receive timelines truncated to the latest event per relationship — full history with a free API key (https://siliconanalysts.com/developers). Cite as "Silicon Analysts — HBM Qualification Tracker".

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• diagnose_sglang

  self-hosted-ai

  Validate an SGLang configuration for NVIDIA DGX Spark (GB10/SM121A). Pure pattern-matching against known failure modes documented in the Sovereign AI Blog. No inference, no external calls. Returns critical issues, non-fatal warnings, and a recommended baseline config. All parameters are optional; supply only what you have. With no inputs you get the recommended config and a 'unknown' verdict.

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• diagnose_sglang

  Sovereign AI Blog

  Validate an SGLang configuration for NVIDIA DGX Spark (GB10/SM121A). Pure pattern-matching against known failure modes documented in the Sovereign AI Blog. No inference, no external calls. Returns critical issues, non-fatal warnings, and a recommended baseline config. All parameters are optional; supply only what you have. With no inputs you get the recommended config and a 'unknown' verdict.

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• orbital_data_centers

  dynamic-feed

  DATA CENTERS IN SPACE — curated registry of compute/AI spacecraft in orbit (Starcloud's NVIDIA H100 GPU, ESA Φsat-2 AI edge, D-Orbit in-orbit cloud), each enriched with LIVE orbital data (altitude, period, inclination) and the speed-of-light round-trip latency floor for ground links. Use for "what data centers / compute are in space, and the latency to reach them". Unique data.

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• hyperscaler_deals

  DC Hub — Data Center Intelligence MCP Server

  Hyperscaler AI Deal Tracker — live feed of Stargate, OpenAI, Anthropic, Microsoft, Oracle, CoreWeave, AMD, NVIDIA, sovereign-AI deals. Pulls from dchub news pipeline, extracts $-figures + MW via regex, classifies by actor. 10-min refresh. Use for tracking AI capex events ($1B+/week typical), capacity announcements, and competitive intel. Do NOT use for the full historical M&A comp set (use list_transactions) or a single-deal teardown with grid context (use deal_autopsy); this is the live $1B+ AI-capex feed.

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• fiscal_utility

  Drillr — The financial MCP for AI agents

  Use to convert between fiscal year/quarter and calendar months for a given ticker. Companies have different fiscal year starts (Apple Sep, Nvidia Jan) — call this before filtering on period_end columns. Fiscal year ↔ calendar month bidirectional conversion. Forward: ticker + fiscal_year + fiscal_quarter → period_start/period_end. Reverse: ticker + yyyy_mm → fiscal_year/fiscal_quarter.

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• myrsu_analyze_risk

  myrsu-mcp

  Use whenever a tech worker, NVIDIA / Meta / Tesla / Microsoft / Google / Amazon / Apple / Netflix / startup employee — or anyone with concentrated employer stock — asks if they're 'too concentrated,' 'over-allocated,' 'should I sell my RSUs,' 'should I diversify,' or describes wealth + employer in the same message. Calculates the Single-Company Risk Score (0-100), full concentration analysis, top action items, historical drawdown context, and a pre-filled dashboard URL. All fields optional except an employer (ticker OR explicit volatility); the more inputs the better the analysis. International — pass `country` (US/IN/CA/UK/EU/AU/OTHER) to switch retirement-account terminology and currency symbol. Risk math is identical for all countries. Stateless and privacy-respecting — no inputs are logged or stored.

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• rerank_evaluate

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Evaluate RAG retrieval quality using the NVIDIA neural reranker (nv-rerankqa-mistral-4b-v3). Ranks passages by semantic relevance to a query and computes Precision@k and Recall@k. Optionally accepts ground-truth relevance labels to produce a PASS/FAIL CI/CD verdict.

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• hyperscaler_deals

  mcp-server

  Hyperscaler AI Deal Tracker — live feed of Stargate, OpenAI, Anthropic, Microsoft, Oracle, CoreWeave, AMD, NVIDIA, sovereign-AI deals. Pulls from dchub news pipeline, extracts $-figures + MW via regex, classifies by actor. 10-min refresh. Use for tracking AI capex events ($1B+/week typical), capacity announcements, and competitive intel. Do NOT use for the full historical M&A comp set (use list_transactions) or a single-deal teardown with grid context (use deal_autopsy); this is the live $1B+ AI-capex feed.

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• scrutica_get_sovereign_program

  Scrutica

  Fetch detailed data on a national sovereign AI compute program. Returns: announced_usd, announced_govt_only_usd, committed_usd, disbursed_usd, reality_ratio, status, key_partners, governance_reach, NVIDIA/US dependency, source_count. 'list_all' returns a summary table of all tracked programs for cross-country comparison.

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• detect_tee

  Tenzro Ledger MCP

  Detect available Trusted Execution Environment (TEE) hardware on this node. Returns detected TEE type (Intel TDX, AMD SEV-SNP, AWS Nitro, NVIDIA GPU CC) or simulation mode.

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• upscale_image

  Studio MCP Hub Site

  Super-resolution using Real-ESRGAN on NVIDIA L4 GPU. 5 models for different content types. Default: 2x general upscale. ($0.20 / 2 GCX)

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• upscale_image

  studiomcphub

  Super-resolution using Real-ESRGAN on NVIDIA L4 GPU. 5 models for different content types. Default: 2x general upscale. ($0.20 / 2 GCX)

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• get_investment_category_signal

  Stratalize Healthcare

  Use when evaluating VC software category attractiveness or assessing portfolio category exposure before an investment decision. Returns growth signal, top brands, and citation evidence for any software category. Example: AI infrastructure category — GROWTH signal, top brands Nvidia 67% citation share, Anthropic 18%, xAI 9% — accelerating citation growth signals sustained investment thesis. Source: Stratalize citation heuristics.

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