AI agents call search_logs to retrieve information from Kestra Python MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The name 'search_logs' strongly implies a retrieval or query operation over log data without modification. Given the context of a Kestra workflow management server and the pattern of sibling tools, this appears to be a read-only operation with no side effects. The empty description prevents higher confidence, but the naming convention and server context support Read classification.
From the tool's definition Tool name 'search_logs' indicates querying/retrieval of log data. Description is empty, limiting confidence. Sibling tools like 'download_execution_logs' and 'follow_execution_logs' on this server are clearly Read operations, suggesting similar intent.
Documented attack patterns abuse exactly the kind of access search_logs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Kestra Python MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for search_logs:
{
"version": "1",
"default": "deny",
"tools": {
"search_logs": {}
}
}search_logs is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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search_logs. It is categorised as a Read tool in the Kestra Python MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Kestra Python MCP Server MCP server in PolicyLayer and add a rule for search_logs: 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 Kestra Python MCP Server. Nothing to install.
search_logs is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the search_logs 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 search_logs. 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.
search_logs is provided by the Kestra Python MCP Server MCP server (kestra-io/mcp-server-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Kestra Python MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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39 Kestra Python MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.