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HTTP Tools is rate-limited at two layers, both using token buckets. Each bucket refills at a fixed rate; you spend tokens as you go. When a bucket empties, the next request gets HTTP_TOOL_RATE_LIMITED and the AI silently moves on (it does NOT retry).

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Layer 1, Per-tenant budget

This is the global cap. If your tenant is making 200 calls a minute spread across tools and agents, you’ll start hitting this limit and the AI will skip non-essential lookups.

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Layer 2, Per-tool budget

Prevents one runaway tool from starving other tools on the same tenant. If your lookup_routing tool gets hammered, check_balance keeps working.

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How the bucket arithmetic works

The bucket is continuously refilling. You don’t have to wait a full second between calls: a full bucket lets you spend up to its capacity at once (60 on the tenant bucket, 30 on a tool bucket), then it refills at the refill rate.

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What the AI sees when limited

The runtime returns:
The AI receives the llm_message as the tool result and continues the conversation. It does NOT auto-retry. From the caller’s perspective the AI just decides it has enough information.

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What the dashboard surfaces

Every invocation row in the Invocations panel includes the remaining tenant-bucket count at the time of the call (in the _meta.rate_limit_remaining field of the response body). Rows that hit a limit are flagged red with the HTTP_TOOL_RATE_LIMITED code.

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Test fires count against your budget

The dashboard’s Send test button runs a real invocation, so it draws from the same per-tenant and per-tool buckets as production calls. There is no separate test allowance. If you hammer Send test while debugging, you can rate-limit your live agent, so test in bursts rather than in a tight loop.

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Asking for a higher quota

Both layers are hard-coded constants in v1. If your use case genuinely needs more (e.g. you run 100+ concurrent calls and every one chains 3-4 HTTP Tool lookups), open a support ticket with:
  • Your tenant ID.
  • Approximate call volume per minute.
  • Average HTTP Tool invocations per call.
We can lift the per-tenant cap on a per-tenant basis.

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Implementation note (for the curious)

Buckets live in the edge function’s module scope (Map<string, Bucket>). Supabase keeps the runtime warm under load, so bucket state survives across requests. Cold starts reset the bucket to full, a corner case where a tenant just over their limit might briefly get one or two extra calls through. We’re comfortable with this drift for v1; if you observe surprising behavior, file it under “we’d like to know.”

Next: Security restrictions

What URLs we block and why.