Get the current status and progress of a reactive review session. Returns: - Session status (active, paused, completed, cancelled, error) - Progress percentage and step counts - Findings count - Telemetry data (elapsed time, tokens used, cache hit rate)
AI agents call get_review_status to retrieve information from Context Engine MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool purely retrieves and queries the state of an existing code review session. It returns read-only status information (session state, progress metrics, telemetry) with no capability to modify, delete, or trigger external operations. It is a straightforward data retrieval operation with no blast radius if misused by an AI agent.
From the tool's definition Tool name 'get_review_status' and description explicitly states it 'Get[s] the current status' and 'Returns' status metrics, progress percentages, step counts, findings count, and telemetry data. No modifications, deletions, or side effects are performed.
Documented attack patterns abuse exactly the kind of access get_review_status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Context Engine MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_review_status:
{
"version": "1",
"default": "deny",
"tools": {
"get_review_status": {}
}
}get_review_status 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.
Get the current status and progress of a reactive review session. Returns: - Session status (active, paused, completed, cancelled, error) - Progress percentage and step counts - Findings count - Telemetry data (elapsed time, tokens used, cache hit rate). It is categorised as a Read tool in the Context Engine MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Context Engine MCP Server MCP server in PolicyLayer and add a rule for get_review_status: 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 Context Engine MCP Server. Nothing to install.
get_review_status 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 get_review_status 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 get_review_status. 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.
get_review_status is provided by the Context Engine MCP Server MCP server (kirachon/context-engine). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Context Engine MCP Server, 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.
50 Context Engine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.