check_deployment_readiness

Pre-flight check for deploy_app: surfaces the caller

Server Manifest MCP manifest-network/manifest-mcp-mono
Category Read
Risk class Low
Parameters 00 required

What check_deployment_readiness does on Manifest MCP

AI agents call check_deployment_readiness to retrieve information from Manifest MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why check_deployment_readiness needs a policy

This tool appears to be a diagnostic/validation check that queries deployment readiness status and returns information to the caller. It performs no write, execute, or destructive operations—it simply surfaces (returns/displays) readiness state. The 'pre-flight check' pattern is standard for read-only validation before allowing other operations.

From the tool's definition Tool description states 'Pre-flight check' which performs validation/inspection without modification. The verb 'surfaces' indicates information retrieval. No descriptions of side effects, state changes, or destructive operations present.

Questions about check_deployment_readiness

What does the check_deployment_readiness tool do? +

Pre-flight check for deploy_app: surfaces the caller. It is categorised as a Read tool in the Manifest MCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on check_deployment_readiness? +

Register the Manifest MCP server in PolicyLayer and add a rule for check_deployment_readiness: 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 Manifest MCP. Nothing to install.

What risk level is check_deployment_readiness? +

check_deployment_readiness is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit check_deployment_readiness? +

Yes. Add a rate_limit block to the check_deployment_readiness 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.

How do I block check_deployment_readiness completely? +

Set action: deny in the PolicyLayer policy for check_deployment_readiness. 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.

What MCP server provides check_deployment_readiness? +

check_deployment_readiness is provided by the Manifest MCP server (manifest-network/manifest-mcp-mono). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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