Snapshot coverage. The page reads toolCalls from the public insights response. These values come from each listed participant's latest submitted transcript snapshot; they are overwritten on a new submission and are not a trailing-30-day time series. The displayed generation date identifies the API snapshot rendered here.

Server grouping. Only exact names matching mcp__server__tool are included. The text between the first and second double-underscore separators is the server key. Calls, attributed tokens, and errors are additive across exact tool rows; distinct-developer counts are not aggregated because the API does not expose a server-level union.

Sample floor. A server must have at least 5 observed calls to enter the ranking. This reduces one-off noise but does not make the sample representative or a statistical benchmark.

Result ceiling. The API returns at most 100 skill/tool-call rows after ranking built-in and MCP tools together. Lower-volume MCP tools may therefore be absent, so the table is a ranked view of returned observations—not a complete registry of every installed or invoked MCP server.

Cohort and attribution limits. Public participation is opt-in and not weighted to represent all AI coding users. Token values belong to the model turn containing each call and are split across calls in multi-tool turns. Do not interpret them as the MCP server's direct execution cost, latency, or resource use.