Replay multiple captured endpoints in parallel across domains.
AI agents invoke apitap_replay_batch to trigger actions in ApiTap. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Replaying captured API endpoints executes real external operations against web services. Since endpoints can include writes, deletes, or other state-changing operations, and this tool runs them in parallel across multiple domains, the blast radius is high — a misconfigured batch replay could trigger numerous unintended side effects across many services simultaneously.
From the tool's definition 'Replay multiple captured endpoints in parallel across domains' — replaying endpoints triggers external HTTP requests to web services, executing operations whose effects depend on the captured endpoint arguments
Documented attack patterns abuse exactly the kind of access apitap_replay_batch gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ApiTap, and nothing reaches the server without passing your rules. This is the rule we recommend for apitap_replay_batch:
{
"version": "1",
"default": "deny",
"tools": {
"apitap_replay_batch": {
"limits": [
{
"counter": "apitap_replay_batch_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}apitap_replay_batch stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Replay multiple captured endpoints in parallel across domains. It is categorised as a Execute tool in the ApiTap MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ApiTap MCP server in PolicyLayer and add a rule for apitap_replay_batch: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches ApiTap. Nothing to install.
apitap_replay_batch is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the apitap_replay_batch rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for apitap_replay_batch. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
apitap_replay_batch is provided by the ApiTap MCP server (n1byn1kt/apitap). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from ApiTap, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
12 ApiTap tools catalogued and risk-classified — across an index of 43,000+ MCP servers.