AI agents call relevant_learnings to retrieve information from Srclight without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Despite the empty description reducing confidence slightly, the tool fits the Read category pattern established by the server (code indexing and search). It retrieves information from the codebase without modifying, deleting, or executing operations. Severity is medium because querying code intelligence could expose sensitive business logic, architecture, or security patterns if an AI agent misuses discovery results.
From the tool's definition Tool name 'relevant_learnings' suggests retrieval or querying of learned patterns/insights from indexed code.
Documented attack patterns abuse exactly the kind of access relevant_learnings gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Srclight, and nothing reaches the server without passing your rules. This is the rule we recommend for relevant_learnings:
{
"version": "1",
"default": "deny",
"tools": {
"relevant_learnings": {}
}
}relevant_learnings is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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relevant_learnings. It is categorised as a Read tool in the Srclight MCP Server, which means it retrieves data without modifying state.
Register the Srclight MCP server in PolicyLayer and add a rule for relevant_learnings: 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 Srclight. Nothing to install.
relevant_learnings 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 relevant_learnings 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 relevant_learnings. 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.
relevant_learnings is provided by the Srclight MCP server (srclight/srclight). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 42 Srclight tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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42 Srclight tools catalogued and risk-classified — across an index of 42,500+ MCP servers.