Check CI workflow status for a branch. Returns overall and per-workflow status.
AI agents call check_ci_status to retrieve information from GitHub MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves CI status information about GitHub workflows without modifying, deleting, or executing any actions. It is purely informational and has no blast radius if misused by an AI agent—the worst outcome would be reading status information that is already public or accessible to the authenticated user.
From the tool's definition Tool name is 'check_ci_status' and description states it 'Check[s] CI workflow status for a branch. Returns overall and per-workflow status.' The verb 'check' and 'returns' indicate a query/retrieval operation with no side effects.
Attacks that exploit this kind of access
Check CI workflow status for a branch. Returns overall and per-workflow status. It is categorised as a Read tool in the GitHub MCP Server MCP Server, which means it retrieves data without modifying state.
Register the GitHub MCP Server MCP server in PolicyLayer and add a rule for check_ci_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 GitHub MCP Server. Nothing to install.
check_ci_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 check_ci_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 check_ci_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.
check_ci_status is provided by the GitHub MCP Server MCP server (rriesco/github-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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