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In one developer’s Claude Code logs, the 90th-percentile total wait for MCP servers to connect was 35.5 seconds per session—even though the median individual connection took 582 milliseconds. The difference matters: a session may wait on several servers, so quick connections can add up. These figures come from one developer’s machine, not a representative benchmark of MCP users.
What the measurements cover
In a report published on September 16, 2026, Achia Cohen analyzed their own Claude Code MCP connection logs. The dataset covered 35 days, from August 13 to September 16, and included 33,599 log files, 38,876 connection attempts, 22 servers, and 2,888 sessions. These are the author’s counts from one machine and one client.
Cohen paired connection-start and capability-established log lines within per-server, per-session logs. The resulting 27,257 clean start-to-established pairs are the basis for the per-connection latency statistics. The report describes the logs as being under ~/Library/Caches/claude-cli-nodejs/<project>/mcp-logs-<server>/; that path is specific to the author’s setup, so check the installed client version rather than assuming it applies to every system.
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The primary source is Cohen’s DEV Community report. The report describes the analysis as one developer’s lived distribution, not a lab benchmark; its sample cannot establish what other developers or MCP clients typically experience.
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Why the session-level wait is longer than an individual connection
Across the 27,257 clean connection pairs, the median connection took 582 milliseconds, the 90th percentile (p90) was 3,678 milliseconds, and the 99th percentile (p99) was 14,049 milliseconds. These values describe individual connections.
At the session level, the median total connection time was 5.9 seconds and p90 was 35.5 seconds. The report gives a median of eight MCP servers per session, so the total wait across a session can be much larger than the typical wait for one connection. A slow tail across multiple configured servers can be more noticeable than the per-connection median suggests.
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What the report found about token refresh and transport
The comparisons below are descriptive results from Cohen’s dataset. They do not establish causes or universal performance rankings.
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| Connections with an in-window token refresh | 3,170 ms | 9,619 ms |
| Connections without an in-window token refresh | 550 ms | 3,400 ms |
| HTTP connections | 676 ms | 3,395 ms |
| stdio connections | 222 ms | 4,693 ms |
Connections with a token refresh during the connection window were slower in this sample. That is an association, not evidence that refresh alone caused the additional latency; other conditions may coincide with refresh.
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The transport figures show a median-versus-tail tradeoff: stdio had the lower median, while HTTP had the lower p90. They do not support a blanket choice between transports. Deployment context matters too—for example, whether an HTTP service is already running or a stdio process must be started.
How to interpret the missing establishment records
Of 38,876 logged attempts, 11,556 (29.7%) did not have a corresponding logged established line. Cohen cautions that log rotation may explain some of the missing records. Treat this as an upper-bound signal of attempts without a recorded establishment, not as a verified MCP connection-failure rate.
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How the timing was bounded
The report capped measurements at the client’s stated 30,000-millisecond timeout so that laptop sleep would not be mistaken for active connection time. In cleanup, the author removed 24 of 27,281 samples. The reported latency distribution is therefore based on the remaining 27,257 clean pairs, with timings bounded by that timeout.
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Cohen’s practical suggestions are useful as diagnostic questions, not as independently tested fixes:
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- Count how many MCP servers are configured, and consider whether you still use all of them.
- Consider making servers that are heavy or needed only occasionally opt-in.
- Check whether slower connections coincide with token refresh, without assuming refresh is the cause.
- Compare both median and tail latency when assessing transports, and account for whether a service is already running or a process must be spawned.
- Inspect logs already available in your setup, while verifying the log location for your client version.
The report does not establish a population-wide norm, a causal effect of OAuth refresh, or an optimal transport for MCP users generally. Cohen explicitly asks readers whether a median of eight configured servers is normal, underscoring that comparisons across developers and clients remain an open question.
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