This record as markdown: /tools/delego-dev-delego/delego-audit-tail.md
What delego_audit_tail does on Pypi:delego
AI agents call delego_audit_tail to retrieve information from Pypi:delego without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why delego_audit_tail is rated Low
The name 'audit_tail' strongly implies reading the tail of an audit log (similar to 'tail -f' on a log file), which is a read operation with no side effects. Given the server context as a policy and audit firewall, an audit tail tool would retrieve recent audit entries. However, the empty description lowers confidence.
From the tool's definition Tool name 'delego_audit_tail' suggests reading/tailing audit logs; description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs delego_audit_tail safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Pypi:delego, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For delego_audit_tail, this is the rule to start with:
delego_audit_tail is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Pypi:delego, apply this rule, and every delego_audit_tail call is checked against it from then on.
Questions about delego_audit_tail
delego_audit_tail is a read tool on the Pypi:delego MCP server. It is categorised as a Read tool in the Pypi:delego MCP Server, which means it retrieves data without modifying state.
Register the Pypi:delego MCP server in PolicyLayer and add a rule for delego_audit_tail: 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:delego. Nothing to install.
delego_audit_tail 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 delego_audit_tail 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 delego_audit_tail. 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.
delego_audit_tail is provided by the Pypi:delego MCP server (pypi:delego). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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