@aiiq/mcp
# @aiiq/mcp
Model Context Protocol server for [AI IQ](https://www.aiiq.org) — query AI model IQ,
rankings, applied-capability domains, benchmarks, and methodology from any MCP client (Claude Code, etc.).
Read-only. Talks to the public AI IQ API over HTTPS; no API key required.
## Install
Requires Node.js 18+. No API key needed. Works in any MCP client.
**Claude Code** (one command):
```bash
claude mcp add aiiq -- npx -y @aiiq/mcp # add --scope user for all projects
```
**Claude Desktop** — edit `claude_desktop_config.json` (Settings → Developer → Edit Config) and add:
```json
{
"mcpServers": {
"aiiq": { "command": "npx", "args": ["-y", "@aiiq/mcp"] }
}
}
```
Then fully quit and reopen the app. (If Node is managed by nvm/asdf, use the absolute path to `npx`
as the `command`, since the desktop app doesn't inherit your shell PATH.)
**Cursor / Windsurf / other clients** — same JSON in the client's MCP config:
```json
{ "mcpServers": { "aiiq": { "command": "npx", "args": ["-y", "@aiiq/mcp"] } } }
```
## Tools
- `list_models` — all public models with IQ, 7 dimension scores, emotional reasoning, rank, cost
- `get_model` — full detail for one model (incl. per-benchmark results)
- `list_rankings` — available leaderboards with ids, names, model counts, and URLs
- `get_ranking` — ordered models for one ranking id
- `list_domains` — applied-capability domains and benchmark counts
- `get_domain` — model composite IQs and benchmark leaderboards for one domain
- `list_benchmarks` — benchmark catalog
- `get_methodology` — how AI IQ is computed
- `compare_models` — side-by-side detail for several models
## Config
- `AIIQ_API_BASE` — override the versioned API base URL (default `https://www.aiiq.org/api/v1`).
A custom value must be the API root that contains paths such as `/models` and `/rankings`.
## Development
```bash
pnpm install
pnpm test
pnpm build
```
## License
MIT
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose: listing models, benchmarks, rankings; getting details for single or multiple models; retrieving ranking order; and explaining methodology. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern with imperative verbs (compare, get, list) and underscore separation, creating a predictable and readable set.
Seven tools is well-scoped for a model intelligence ranking service, covering listing, detailed retrieval, comparison, and methodology without being sparse or excessive.
The tool surface covers all essential operations: listing all models, benchmarks, and rankings; retrieving individual model details; comparing models; and understanding the methodology. No obvious gaps for a read-only reference service.