Set the active AWX environment
AI agents use env_set_active to create or update resources in Pypi:awx — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Pypi:awx environment.
This tool changes which AWX environment is active, affecting the operational context for subsequent tool calls. While reversible (you can switch to a different environment), it modifies system state and could cause confusion or unintended operations if the wrong environment is activated.
From the tool's definition The tool name 'env_set_active' and description 'Set the active AWX environment' indicates it modifies configuration state by selecting which AWX environment is currently active. This is a reversible state change rather than data deletion.
Documented attack patterns abuse exactly the kind of access env_set_active gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pypi:awx, and nothing reaches the server without passing your rules. This is the rule we recommend for env_set_active:
{
"version": "1",
"default": "deny",
"tools": {
"env_set_active": {
"limits": [
{
"counter": "env_set_active_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}env_set_active stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Set the active AWX environment. It is categorised as a Write tool in the Pypi:awx MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Pypi:awx MCP server in PolicyLayer and add a rule for env_set_active: 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 Pypi:awx. Nothing to install.
env_set_active is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the env_set_active 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 env_set_active. 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.
env_set_active is provided by the Pypi:awx MCP server (SurgeX-Labs/awx-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pypi:awx, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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50 Pypi:awx tools catalogued and risk-classified — across an index of 43,000+ MCP servers.