MCP performance and rate limits
Loomi Connect MCP applies rate limits and caches responses to protect service stability. This page covers performance considerations, how limits and cache behave, and what your client should do.
Performance
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Dashboard-level APIs: Tools call the same APIs that power the Bloomreach UI, not dedicated backend endpoints. Responses can be slower or less consistent than a production API.
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Analytics latency: Ad-hoc analytics computations can take 10 to 30 seconds on large datasets.
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Cross-project calls: Cross-project overview tools make one API call per project and can be slow on organizations with many projects.
Rate limits
Rate limits prevent burst traffic from overwhelming downstream systems.
A single request can be subject to multiple limits. All applicable limits must pass before the tool runs.
If a request exceeds a limit, the MCP returns an error with retry guidance. Back off and retry once the suggested wait time has passed.
WarningThe server returns the following error message in response if a tool call is rate limited:
Too many requests: rate limit reached for key '<key>' (<limit>). Retry after ~<N> second(s).
Downstream project APIs impose their own limits as well. Handle throttling errors even after a request passes MCP-level checks.
Write tool limits
Write tools carry a stricter limit on top of the global one, because a mutation is harder to undo than a read. A write tool allows 1 call per 5 seconds and 10 calls per minute, and the global limit of 1 call per second and 60 calls per minute still applies. Space out consecutive writes rather than issuing them in a tight loop.
This applies to Data hub write tools alongside the Marketing and Search write tools. The Data hub write tools that create and update an item collection are documented in Item collections tools, and the tool that applies a configuration change list is documented in Item collection configuration tools.
Deletes are limited more tightly still, at 1 call per 10 seconds and 10 calls per minute. Deleting an item collection falls under that limit.
Handle rate limit errors
Apply retry and backoff logic in your client. Exponential backoff is a common pattern.
Caching
Loomi Connect MCP caches responses to reduce load on the Marketing API and improve latency. Expect some reads to come from cache. If your workflow depends on near-real-time data, account for a short delay between when a change is written and when it becomes visible in MCP reads.
Cache lifetimes
Cache lifetimes vary by resource type:
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Resources that change frequently are cached for only a few seconds.
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More stable metadata caches for longer.
Updated 3 days ago

