Arabic AI Advisor

Recommends Arabic AI models, datasets and tools from the Arabic AI Atlas, a curated catalogue with Hugging Face download metrics.

When to use

• The user needs an Arabic (or dialect-specific) LLM, ASR, TTS, OCR or embedding model.
• The user asks which Arabic dataset, benchmark or tool fits a task.
• The user has constraints such as a license, a dialect, or running on-device.

Procedure

1. Call the MCP tool recommend with the task and the type the user wants (llm, asr, tts, ocr, embedding for a model; dataset, benchmark or tool otherwise), plus dialect, on_device and license_filter when the user gave them. Example: recommend(task="tts", type="tts", on_device=true, license_filter="open").
2. If the MCP tools are unavailable, read ${CLAUDE_PLUGIN_ROOT}/dist/atlas.json and filter entries by tasks.
3. For breadth, or when recommend returns too little, call search (and get for one entry by id). To trace what a model was built from or what was built on it, call lineage(id=...); entries carry an optional base_model list (HF ids, atlas ids or from-scratch).
4. Format the answer as described below.

Answer format

Give 3 ranked options. For each: name, org, license, dialects, size, a one-line why, and a link. Then state the atlas generated_at date.

If nothing fits, say: "Not in the atlas: I found no entry matching this request." Do not guess.

Rules

• Never invent entries; only report what the atlas returns.
• Prefer open licenses when the user does not say.
• Say when metrics (downloads, size, license) are missing.
• If two options tie, prefer the one updated more recently.

Valid values

Parameter	Values
type	llm, asr, tts, ocr, embedding, dataset, benchmark, tool, agent-skill, org, paper
country	SA, AE, EG, LB, QA, JO, MA, TN, KW, OM, BH, DZ, LY, SD, IQ, SY, YE, PS, MR, SO, DJ, KM, INTL
modality	text, speech, vision, multimodal, none
dialect	msa, egy, gulf, lev, magh, iraqi, sudanese, yemeni, classical, mixed
base_model	list of HF ids, atlas ids, or from-scratch (model types only)
task (examples)	chat, tts, asr, ocr, embedding, translation