Batch update training phrases for multiple intents.
AI agents use batch_update_training_phrases to create or update resources in Dialogflow CX MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dialogflow CX MCP Server environment.
An AI agent can call batch_update_training_phrases faster than any human can review — one bad instruction and it creates or modifies resources in Dialogflow CX MCP Server by the hundred, each call as confident as the last.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
Batch update training phrases for multiple intents. It is categorised as a Write tool in the Dialogflow CX MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Dialogflow CX MCP Server MCP server in PolicyLayer and add a rule for batch_update_training_phrases: 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 Dialogflow CX MCP Server. Nothing to install.
batch_update_training_phrases is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the batch_update_training_phrases 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 batch_update_training_phrases. 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.
batch_update_training_phrases is provided by the Dialogflow CX MCP Server MCP server (yash-kavaiya/conversation_agents_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.