AI & Machine Learning
aicomputeradar.dev
Tracks trending AI models and provides tools to find which models run on specific GPUs/Macs, compare GPU rental prices, list hardware profiles, and surface a weekly model pick.
ENDPOINT 1
https://aicomputeradar.dev/api/mcp
MCP server metadata
- Name
- ai-compute-radar
- Version
- 1.2.0
AI Compute Radar exposes measured AI-model momentum, hardware-fit verdicts and GPU rental prices. Every result carries meta.source (live = measured, fallback = demo fixtures) and meta.collectedAt — repeat the collection time when quoting a number. Data is CC BY 4.0: attribute 'AI Compute Radar (https://aicomputeradar.dev)'.
Known tools 5
trending_modelsTracked 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.
Inferred read-onlyfind_fitWhich tracked models run on a given GPU or Mac: measured GGUF weights + computed context cache + runtime overhead versus usable memory.
Inferred read-onlylist_hardwareCurated GPU and Mac profiles the fit engine knows — ids, memory, usable memory after margins, bandwidth.
Inferred read-onlyweekly_pickThe 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.
Inferred read-onlyCONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.ai-compute-radar]
url = "https://aicomputeradar.dev/api/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"ai-compute-radar": {
"type": "http",
"url": "https://aicomputeradar.dev/api/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: ai-compute-radar
Remote MCP URL: https://aicomputeradar.dev/api/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"ai-compute-radar": {
"url": "https://aicomputeradar.dev/api/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"ai-compute-radar": {
"type": "http",
"url": "https://aicomputeradar.dev/api/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "ai-compute-radar",
"transport": "streamable-http",
"url": "https://aicomputeradar.dev/api/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Loading Trust v2 evidence…
Checking the associated registrable domain. The BuiltWith key remains server-side.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.