AI agents call manage_group as a supporting operation in Kestra Python MCP Server workflows.
With an empty description, the exact behavior of 'manage_group' is unknown. Based on the name alone, it likely involves creating, updating, or deleting groups (possibly user/permission groups within Kestra). 'Manage' implies write or administrative operations, but without evidence, confidence is low. Defaulting to Write category behavior is plausible, but cannot confirm severity or category with certainty.
From the tool's definition Tool name is 'manage_group' but description is empty or uninformative. No description provided to clarify what this tool does.
Documented attack patterns abuse exactly the kind of access manage_group 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 manage_group:
{
"version": "1",
"default": "deny",
"tools": {
"manage_group": {
"limits": [
{
"counter": "manage_group_rate",
"window": "minute",
"max": 60,
"scope": "grant"
}
]
}
}
}manage_group gets a rate cap, and everything else on the server is denied unless you say otherwise.
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manage_group. It is categorised as a Other tool in the Kestra Python MCP Server MCP Server, which means it performs auxiliary operations.
Register the Kestra Python MCP Server MCP server in PolicyLayer and add a rule for manage_group: 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.
manage_group is a Other tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the manage_group 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 manage_group. 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.
manage_group 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.