Convert text to speech using Deepgram
AI agents invoke text_to_speech to trigger actions in Deepgram MCP Server. 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.
This tool triggers an external operation (Deepgram's TTS API) that synthesizes audio from text. It goes beyond a simple read/write — it executes an AI model inference pipeline on an external service. Misuse could involve generating deceptive or manipulative audio content, making it medium severity.
From the tool's definition Convert text to speech using Deepgram
Attacks that exploit this kind of access
Convert text to speech using Deepgram. It is categorised as a Execute tool in the Deepgram MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Deepgram MCP Server MCP server in PolicyLayer and add a rule for text_to_speech: 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 Deepgram MCP Server. Nothing to install.
text_to_speech 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 text_to_speech 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 text_to_speech. 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.
text_to_speech is provided by the Deepgram MCP Server MCP server (reddheeraj/deepgram-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
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