# AI Compute Radar (remote · aicomputeradar.dev)

Which open models fit your GPU or Mac, measured. Model momentum, GPU rental prices, weekly pick.

- Trust score: 68/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- remote · `aicomputeradar.dev`: 68/100 (this document), [markdown](https://verifymcp.io/servers/dev-aicomputeradar-ai-compute-radar/api-mcp.md), [page](https://verifymcp.io/servers/dev-aicomputeradar-ai-compute-radar/api-mcp)

## Channel facts

- Endpoint: `https://aicomputeradar.dev/api/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.2.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-20.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 5 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 79/100
  - AI-judged instruction clarity (excellent).
  - Tool/resource definitions use about 563 tokens (~112/item across 5 items; 5 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 7/100
  - Stability observed for 2 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the AI Compute Radar MCP server?

AI Compute Radar is a hosted endpoint at https://aicomputeradar.dev/api/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http dev-aicomputeradar-ai-compute-radar 'https://aicomputeradar.dev/api/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "dev-aicomputeradar-ai-compute-radar": {
      "url": "https://aicomputeradar.dev/api/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "dev-aicomputeradar-ai-compute-radar": {
      "type": "http",
      "url": "https://aicomputeradar.dev/api/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.dev-aicomputeradar-ai-compute-radar]
url = "https://aicomputeradar.dev/api/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "dev-aicomputeradar-ai-compute-radar": {
      "type": "remote",
      "url": "https://aicomputeradar.dev/api/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add dev-aicomputeradar-ai-compute-radar --url 'https://aicomputeradar.dev/api/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  dev-aicomputeradar-ai-compute-radar:
    url: "https://aicomputeradar.dev/api/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "dev-aicomputeradar-ai-compute-radar": {
      "Transport": "http",
      "Url": "https://aicomputeradar.dev/api/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add dev-aicomputeradar-ai-compute-radar -t streamable-http -u 'https://aicomputeradar.dev/api/mcp'
```

### Other

```json
{
  "mcpServers": {
    "dev-aicomputeradar-ai-compute-radar": {
      "type": "http",
      "url": "https://aicomputeradar.dev/api/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-19 (score 68, +1)

- [functional improvement] Stability: unverified → 0.03

### 2026-09-18 (score 67)

First indexed and scored.

## MCP tools (5)

### `trending_models` (~97 tokens)

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 parameters:

- `limit` (integer): How many models to return (default 12).
- `slug` (string): Return a single model by slug.

### `find_fit` (~149 tokens)

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 parameters:

- `context` (integer): Context length in tokens (default 8192).
- `hardware` (string, required): Hardware id or page slug, e.g. rtx-4090, mac-studio-m3-ultra-96gb.
- `kv` (string): KV-cache quantization (default f16).
- `model` (string): Restrict to one model slug.

### `gpu_prices` (~80 tokens)

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. The index describes what prices did; it never forecasts.

### `list_hardware` (~38 tokens)

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.

### `weekly_pick` (~124 tokens)

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 parameters:

- `week` (string): ISO week label of a past issue, e.g. 2026-w37 (default: the current issue).

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/dev-aicomputeradar-ai-compute-radar/api-mcp#diagnostics

## Score history

- 2026-09-20: 68
- 2026-09-19: 68
- 2026-09-18: 67

## Common questions

### What is the AI Compute Radar MCP server?

AI Compute Radar is an MCP server listed in the public MCP registry as dev.aicomputeradar/ai-compute-radar. Which open models fit your GPU or Mac, measured. Model momentum, GPU rental prices, weekly pick. This page covers its hosted endpoint (https://aicomputeradar.dev/api/mcp).

### Is the AI Compute Radar MCP server safe to use?

AI Compute Radar scores 68 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the AI Compute Radar MCP server expose?

AI Compute Radar exposes 5 tools: trending_models, find_fit, gpu_prices, list_hardware, weekly_pick. Their descriptions and schemas cost roughly 488 tokens of context every time the server is loaded.

### Does the AI Compute Radar MCP server require authentication?

No. We connected to AI Compute Radar without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the AI Compute Radar MCP server still maintained?

AI Compute Radar is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://aicomputeradar.dev/api/mcp
- Website: https://aicomputeradar.dev/developers
- Changelog RSS feed: https://verifymcp.io/servers/dev-aicomputeradar-ai-compute-radar/api-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/dev-aicomputeradar-ai-compute-radar/api-mcp.json
- HTML version of this page: https://verifymcp.io/servers/dev-aicomputeradar-ai-compute-radar/api-mcp