AI Compute Radar
dev.aicomputeradar/ai-compute-radar · 1.2.0
Which open models fit your GPU or Mac, measured. Model momentum, GPU rental prices, weekly pick.
Nobody here has read this server's code, because it publishes none. The description above is the maker's own, from the registry. A connection test shows whether it answers and what tools it says it has; it never calls a tool, so it cannot show what one does with your data.
Where it sits in the directory's order
What can be seen from outside, weighed as the directory publishes.
Observable signals: 45 of 100 points (at most 60 here)
| Input | Points | What was seen |
|---|---|---|
| Source published | held at 0 | No entry here publishes source: that is what puts it in this directory. |
| Licence stated | held at 0 | With no files, there is nothing for a licence to be stated in or held against. |
| Advisory state | held at 0 | Advisory databases index packages, and these entries publish none, so there is nothing to look up. |
| Auth declared | 0 of 15 | The registry entry declares no key. That is what it declares, not a finding that it has no protection. |
| Latest connection test reached it | 20 of 20 |
Where it answers
https://aicomputeradar.dev/api/mcpstreamable-http
Connection test
The MCP handshake, then a request for the tool list, with no key and no data of yours. Run nightly, and by anyone, at most once every ten minutes per server.
It completed the handshake and listed 5 tools.
- Protocol
- 2025-06-18
- Calls itself
- ai-compute-radar 1.2.0
- Handshake time
- 186 ms
- HTTP status
- 200
The tools it lists (5, as of 11 hours ago)
The tool-description rules found nothing in these descriptions. They look for instructions aimed at a model and for hidden characters; they cannot see what a tool does when it runs.
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. Models still collecting a week of history have heat=null and rank after scored ones.
find_fitWhich 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.
gpu_pricesMedian 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), Clore.ai's median for the same class (a second marketplace, never blended), and the AWS, Azure and Oracle Cloud pay-as-you-go list prices per GPU-hour, each with the instance type, VM size or bare-metal shape the
list_hardwareCurated GPU and Mac profiles the fit engine knows — ids, memory, usable memory after margins, bandwidth. Use an id with find_fit.
weekly_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. Pass week (e.g. 2026-w37) for a past issue. issue is null until the first issue is published.
How this entry becomes a listing
For the maker. The catalogue lists what it can read, and this server publishes nothing to read yet. There are two routes, and only the first is open today.
Publish the source Open today
- Put the server's source in a public repository on github.com, with a licence.
- Keep a server.json in that repository naming this server,
dev.aicomputeradar/ai-compute-radar, and declare the repository in it:"repository": { "url": "https://github.com/owner/repo", "source": "github" }, adding"subfolder"when the server lives in a folder. - Publish that version to the official MCP registry.
- The nightly registry sweep records the declaration. This page stays, dated, and says the source is declared but not yet read.
- The catalogue reads declared repositories at a pinned commit, in batches run by hand, and lists the servers that meet the batch's rules (among them a server.json at that commit naming the server, an https endpoint and a licence). When it lists this server, this page links to the listing. There is no schedule, so no date can be promised.
List it through the maker studio Not open yet
From the official MCP registry, last updated there 20 days ago. The registry entry · aicomputeradar.dev