Semantic search over checkpoint titles and summaries.
AI agents call search_checkpoints 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 semantic search functionality, which retrieves and queries data about checkpoints without creating, modifying, deleting, or executing any operations. It is a read-only query interface with no side effects, placing it firmly in the Read category with low severity.
From the tool's definition Tool name is 'search_checkpoints' and description states 'Semantic search over checkpoint titles and summaries' — this is a query/retrieval operation with no modification, deletion, or code execution.
Documented attack patterns abuse exactly the kind of access search_checkpoints 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 search_checkpoints:
{
"version": "1",
"default": "deny",
"tools": {
"search_checkpoints": {}
}
}search_checkpoints is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Semantic search over checkpoint titles and summaries. 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 search_checkpoints: 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.
search_checkpoints 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 search_checkpoints 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 search_checkpoints. 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.
search_checkpoints 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.
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29 Local Rag tools catalogued and risk-classified — across an index of 43,000+ MCP servers.