Initialize evolution process with configuration and seed prompt
AI agents invoke gepa_start_evolution to trigger actions in Prompt Auto-Optimizer MCP. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
gepa_start_evolution triggers real processes with real consequences. An agent gone sideways doesn't fire it once — it starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
Initialize evolution process with configuration and seed prompt. It is categorised as a Execute tool in the Prompt Auto-Optimizer MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Prompt Auto-Optimizer MCP server in PolicyLayer and add a rule for gepa_start_evolution: 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 Prompt Auto-Optimizer MCP. Nothing to install.
gepa_start_evolution is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the gepa_start_evolution 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 gepa_start_evolution. 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.
gepa_start_evolution is provided by the Prompt Auto-Optimizer MCP server (sloth-wq/prompt-auto-optimizer-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.