AI agents call explain_error to retrieve information from Proxima without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool appears to fetch or analyze error messages/information for debugging purposes, which is a read-only operation. Even if it calls underlying AI models, it does not create, modify, execute external operations, or delete data. The lack of descriptive text reduces confidence from high to medium-high, but the function name and server context strongly suggest informational retrieval.
From the tool's definition Tool name 'explain_error' suggests retrieval and analysis of error information. The empty description limits confidence, but the naming pattern and sibling tools (ask_*, analyze_*) on this AI gateway server indicate this is a query/retrieval operation without…
Documented attack patterns abuse exactly the kind of access explain_error gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Proxima, and nothing reaches the server without passing your rules. This is the rule we recommend for explain_error:
{
"version": "1",
"default": "deny",
"tools": {
"explain_error": {}
}
}explain_error is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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explain_error. It is categorised as a Read tool in the Proxima MCP Server, which means it retrieves data without modifying state.
Register the Proxima MCP server in PolicyLayer and add a rule for explain_error: 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 Proxima. Nothing to install.
explain_error 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 explain_error 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 explain_error. 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.
explain_error is provided by the Proxima MCP server (zen4-bit/proxima). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 50 Proxima tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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50 Proxima tools catalogued and risk-classified — across an index of 42,500+ MCP servers.