Find the best file and location to insert new code or docs. Returns semantically appropriate insertion points with anchors for precise placement. Use this before adding a new function to find which file and position it belongs in.
AI agents call write_relevant to retrieve information from Local Rag without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool performs a semantic search/query to find appropriate insertion points — it only reads and analyzes existing code to return recommendations. It does not write, modify, or execute anything itself. The word 'Returns' confirms it is a read/query operation.
From the tool's definition Find the best file and location to insert new code or docs. Returns semantically appropriate insertion points with anchors for precise placement.
Documented attack patterns abuse exactly the kind of access write_relevant gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Local Rag, and nothing reaches the server without passing your rules. This is the rule we recommend for write_relevant:
{
"version": "1",
"default": "deny",
"tools": {
"write_relevant": {}
}
}write_relevant is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Find the best file and location to insert new code or docs. Returns semantically appropriate insertion points with anchors for precise placement. Use this before adding a new function to find which file and position it belongs in. It is categorised as a Read tool in the Local Rag MCP Server, which means it retrieves data without modifying state.
Register the Local Rag MCP server in PolicyLayer and add a rule for write_relevant: 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 Local Rag. Nothing to install.
write_relevant 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 write_relevant 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 write_relevant. 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.
write_relevant is provided by the Local Rag MCP server (thewinci/mimirs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Local Rag, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
29 Local Rag tools catalogued and risk-classified — across an index of 43,000+ MCP servers.