393 tokens across 3 tools — lean (< 1K). Measured 2026-08-16 under methodology v1.0.
| server (self-reported) | mysql_mcp_server v1.29.0 |
| status | measured |
| tokenizer | tiktoken / o200k_base |
| launch command | uvx --from mysql-mcp-server mysql_mcp_server |
| isolation | docker · ghcr.io/astral-sh/uv:python3.12-bookworm-slim · network bridge · network enabled for package fetch; clean FS, no host credentials |
| env vars supplied | MYSQL_HOST, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE |
| canonical SHA-256 | 48f53cd914e3137feabfb3087abdb3bb54df46907d605a4cf97fac272bba2afb |
| category | community |
| source | https://github.com/designcomputer/mysql_mcp_server |
| tool | tokens | share | description | schema |
|---|---|---|---|---|
| get_table_sample | 139 | 35.4% | 47 | 61 |
| get_schema_info | 133 | 33.8% | 68 | 34 |
| execute_sql | 119 | 30.3% | 58 | 32 |
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/mysql/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.