Suggest reviewers for target or changed files from local git authorship, recent edits, and code-graph co-change ownership. Does not contact GitHub or external services.
AI agents call kage_reviewers to retrieve information from Kage without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool reads local git history and code-graph data to suggest reviewers. It only retrieves and analyzes existing data without modifying anything or triggering external operations. Explicitly states it does not contact external services. Low severity as it only surfaces read-only metadata about code authorship.
From the tool's definition Suggest reviewers for target or changed files from local git authorship, recent edits, and code-graph co-change ownership. Does not contact GitHub or external services.
Documented attack patterns abuse exactly the kind of access kage_reviewers gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Kage, and nothing reaches the server without passing your rules. This is the rule we recommend for kage_reviewers:
{
"version": "1",
"default": "deny",
"tools": {
"kage_reviewers": {}
}
} kage_reviewers 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.
Suggest reviewers for target or changed files from local git authorship, recent edits, and code-graph co-change ownership. Does not contact GitHub or external services. It is categorised as a Read tool in the Kage MCP Server, which means it retrieves data without modifying state.
Register the Kage MCP server in PolicyLayer and add a rule for kage_reviewers: 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 Kage. Nothing to install.
kage_reviewers 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 kage_reviewers 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 kage_reviewers. 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.
kage_reviewers is provided by the Kage MCP server (@kage-core/kage-graph-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Kage, 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.
62 Kage tools catalogued and risk-classified — across an index of 43,000+ MCP servers.