AI agents call list_examples to retrieve information from Ilograph without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool appears to list or enumerate examples within the Ilograph documentation system. Listing operations are Read operations that retrieve data without side effects. No modification, deletion, or code execution capability is evident.
From the tool's definition Tool name 'list_examples' indicates a listing/enumeration operation. No description provided, but sibling tools like 'fetch_example' and context of documentation access suggest this retrieves example data.
Attacks that exploit this kind of access
list_examples. It is categorised as a Read tool in the Ilograph MCP Server, which means it retrieves data without modifying state.
Register the Ilograph MCP server in PolicyLayer and add a rule for list_examples: 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 Ilograph. Nothing to install.
list_examples 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 list_examples 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 list_examples. 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.
list_examples is provided by the Ilograph MCP server (quincymillerdev/ilograph-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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