MCP Radar
MCP Server

AI Compute Radar

dev.aicomputeradar/ai-compute-radar
AI & Agents Cloud & Infrastructure Data & Analytics Public & reachable MCP 2025-11-25

What this MCP does

Evaluates which tracked AI models fit specific GPUs or Macs and provides model trends, GPU rental prices, and weekly recommendations.

Capabilities

Tools

5 tools
find_fit
Find models that fit a machine
Which tracked models run on a given GPU or Mac: measured GGUF weights + computed context cache + runtime overhead versus usable memory. Returns the best recommendation and every verdict (EXCELLENT/GOOD/TIGHT/OFFLOAD_REQUIRED/NOT_RECOMMENDED/UNKNOWN) with plain-language reasons. Get hardware ids from list_hardware.
Input schema 
{'type': 'object', '$schema': 'https://json-schema.org/draft/2020-12/schema', 'required': ['hardware'], 'properties': {'kv': {'enum': ['f16', 'q8_0', 'q4_0'], 'type': 'string', 'description': 'KV-cache quantization (default f16).'}, 'model': {'type': 'string', 'description': 'Restrict to one model slug.'}, 'context': {'type': 'integer', 'maximum': 1048576, 'minimum': 512, 'description': 'Context length in tokens (default 8192).'}, 'hardware': {'type': 'string', 'description': 'Hardware id or page slug, e.g. rtx-4090, mac-studio-m3-ultra-96gb.'}}}
gpu_prices
GPU rental prices
Median verified on-demand rental price per GPU class on Vast.ai (USD per hour), with min/p75 and offer counts, the collection timestamp, and per class the Rent Index: this week's median against last week and against the first week collected, a trend word, and the days excluded as marketplace glitches, plus RunPod's lowest posted on-demand price per class (a list price, not a median) and Clore.ai's median for the same class (a second marketplace, never blended). The index describes what prices did; it never forecasts.
Input schema 
{'type': 'object', '$schema': 'https://json-schema.org/draft/2020-12/schema', 'properties': {}}
list_hardware
List hardware profiles
Curated GPU and Mac profiles the fit engine knows — ids, memory, usable memory after margins, bandwidth. Use an id with find_fit.
Input schema 
{'type': 'object', '$schema': 'https://json-schema.org/draft/2020-12/schema', 'properties': {}}
trending_models
Trending models
Tracked AI models ranked by Heat Score (0–100, weighted percentiles of measured Hugging Face/OpenRouter signals) with the raw signals, local-run facts (GGUF size, quantization) and links. Models still collecting a week of history have heat=null and rank after scored ones.
Input schema 
{'type': 'object', '$schema': 'https://json-schema.org/draft/2020-12/schema', 'properties': {'slug': {'type': 'string', 'description': 'Return a single model by slug.'}, 'limit': {'type': 'integer', 'maximum': 100, 'minimum': 1, 'description': 'How many models to return (default 12).'}}}
weekly_pick
Pick of the week
The current pick of the week: one tracked model chosen by a published rule (largest counted Heat Score rise among models that run comfortably on a consumer card of up to 24 GB), with the numbers frozen at selection time, a device-by-device fit ladder and the written report including its caveats. Pass week (e.g. 2026-w37) for a past issue. issue is null until the first issue is published.
Input schema 
{'type': 'object', '$schema': 'https://json-schema.org/draft/2020-12/schema', 'properties': {'week': {'type': 'string', 'pattern': '^\\d{4}-w\\d{2}$', 'description': 'ISO week label of a past issue, e.g. 2026-w37 (default: the current issue).'}}}
History

Recent tool changes

Changed
gpu_prices
Sept. 25, 2026, 2:50 a.m.
Changed
gpu_prices
Sept. 23, 2026, 2:41 a.m.
Added
weekly_pick
Sept. 19, 2026, 2:40 a.m.
Added
list_hardware
Sept. 19, 2026, 2:40 a.m.
Added
gpu_prices
Sept. 19, 2026, 2:40 a.m.
Added
find_fit
Sept. 19, 2026, 2:40 a.m.
Added
trending_models
Sept. 19, 2026, 2:40 a.m.
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