Run test suites and return results with failures and coverage. !! DO NOT USE for local-app "tests for my changes" flows !! This tool sends the run to the SaaS backend which REJECTS private/localhost URLs ("IPv6 address is private / reserved"). It only works when base_url points at a PUBLIC, non-l...
Risk signalsAccepts URL/endpoint input (base_url)
Part of the Keploy server.
Free to start. No card required.
AI agents invoke run_and_report to trigger processes or run actions in Keploy. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
run_and_report can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"run_and_report": {
"limits": [
{
"counter": "run_and_report_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Keploy policy for all 103 tools.
These attack patterns abuse exactly the kind of access run_and_report gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Run test suites and return results with failures and coverage. !! DO NOT USE for local-app "tests for my changes" flows !! This tool sends the run to the SaaS backend which REJECTS private/localhost URLs ("IPv6 address is private / reserved"). It only works when base_url points at a PUBLIC, non-loopback address (a staging/prod deployment). For local-app testing, use record_sandbox_test / replay_sandbox_test instead — they drive the keploy local agent which happily records against http://localhost.. It is categorised as a Execute tool in the Keploy MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Keploy MCP server in PolicyLayer and add a rule for run_and_report: 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 Keploy. Nothing to install.
run_and_report 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 run_and_report 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 run_and_report. 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.
run_and_report is provided by the Keploy MCP server (https://api.keploy.io/client/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 103 Keploy tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.