AI agents call get_agent to retrieve information from Pypi:asqav without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves or queries information about an AI agent's configuration or metadata. It has no side effects, does not modify state, and does not trigger actions. It fits the Read category. Severity is low because exposure of agent metadata, while potentially informative to an attacker, does not directly enable system compromise or data destruction without further exploitation of other tools.
From the tool's definition Tool name is 'get_agent' and description states 'Get details for a specific AI agent' — purely a retrieval operation with no modification, deletion, or execution of external operations.
Documented attack patterns abuse exactly the kind of access get_agent gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pypi:asqav, and nothing reaches the server without passing your rules. This is the rule we recommend for get_agent:
{
"version": "1",
"default": "deny",
"tools": {
"get_agent": {}
}
}get_agent is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get details for a specific AI agent. It is categorised as a Read tool in the Pypi:asqav MCP Server, which means it retrieves data without modifying state.
Register the Pypi:asqav MCP server in PolicyLayer and add a rule for get_agent: 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:asqav. Nothing to install.
get_agent 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 get_agent 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 get_agent. 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.
get_agent is provided by the Pypi:asqav MCP server (jagmarques/asqav-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pypi:asqav, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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15 Pypi:asqav tools catalogued and risk-classified — across an index of 43,000+ MCP servers.