364 tokens across 6 tools — lean (< 1K). Measured 2026-08-16 under methodology v1.0.
| server (self-reported) | Browserbase MCP Server v3.0.0 |
| status | measured |
| tokenizer | tiktoken / o200k_base |
| launch command | npx -y @browserbasehq/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 | BROWSERBASE_API_KEY, BROWSERBASE_PROJECT_ID |
| canonical SHA-256 | 1dc53461369d7cb64ea8151f33283db371951cf44289471f6156e35cd1ae28bb |
| category | vendor-official |
| source | https://github.com/browserbase/mcp-server-browserbase |
| tool | tokens | share | description | schema |
|---|---|---|---|---|
| act | 69 | 19.0% | 6 | 44 |
| observe | 69 | 19.0% | 6 | 44 |
| navigate | 67 | 18.4% | 4 | 44 |
| extract | 58 | 15.9% | 5 | 34 |
| start | 50 | 13.7% | 7 | 24 |
| end | 49 | 13.5% | 6 | 24 |
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/browserbase/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.