Call a captured API endpoint and return live data.
AI agents invoke apitap_replay 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.
This tool executes real API calls against external web services and returns live data. The effects depend entirely on what endpoint is being called — it could read data, but it could equally trigger writes, deletions, or other side effects on the target service. Since the blast radius spans potentially any operation on any captured endpoint, Execute is the appropriate category with high severity.
From the tool's definition Call a captured API endpoint and return live data
Documented attack patterns abuse exactly the kind of access apitap_replay 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:
{
"version": "1",
"default": "deny",
"tools": {
"apitap_replay": {
"limits": [
{
"counter": "apitap_replay_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}apitap_replay 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.
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Call a captured API endpoint and return live data. 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: 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 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 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. 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 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.