4,691 tokens across 4 tools — light (1–5K). Measured 2026-08-16 under methodology v1.0.
| server (self-reported) | huggingface.co/mcp v0.4.9 |
| status | measured |
| tokenizer | tiktoken / o200k_base |
| launch command | npx -y mcp-remote https://huggingface.co/mcp |
| isolation | docker · public.ecr.aws/docker/library/node:22-slim · network bridge · network enabled for package fetch; clean FS, no host credentials |
| env vars supplied | none |
| canonical SHA-256 | b269a72bb6340ebfd5cf8170399b2606a9d7ea88b2277cfd6ca3511cec51a980 |
| category | vendor-official |
| source | https://github.com/huggingface/hf-mcp-server |
| tool | tokens | share | description | schema |
|---|---|---|---|---|
| hf_whoami | 1,948 | 41.5% | 30 | 26 |
| hf_fs | 1,924 | 41.0% | 966 | 87 |
| hub_repo_details | 453 | 9.7% | 76 | 327 |
| hub_repo_search | 364 | 7.8% | 38 | 278 |
Each tool is tokenized on its own, so the parts do not sum exactly to the whole: the array adds its own brackets and commas, and the tokenizer merges tokens across object boundaries. The badge number is always the count of the whole array, never a sum of parts.
npx -y mcp-context-cost verify results/huggingface/measurement.json
That re-tokenizes the published capture and checks the count and the hash. If it disagrees with the badge, the badge is wrong — open an issue and it gets corrected.