We just went live with the SigmaMind MCP Server, and we re on a mission to end "infrastructure hell" for voice developers.
For the last year at SigmaMind (YC S22), we ve watched builders struggle to stitch together telephony, low-latency models, and fragmented APIs. Today, we re changing that. We ve built a way to configure and deploy production-grade voice agents directly from your IDE (Cursor, Claude Code, etc.) using the Model Context Protocol. No more manual glue - just one prompt to connect your model, pick a voice, and get a live phone number.
Hey everyone! With the landscape for building voice agents shifting lately, it feels like we re moving away from heavy, manual API orchestration toward something more streamlined.
How you re currently architecting voice agents. Specifically: Have you used the Model Context Protocol (MCP) to build or provide real-time data/context to your voice agents? Does it actually streamline your tool-calling, or is it more trouble than it's worth?
Would love to hear what's working (and what's breaking) in your current workflow. Drop your thoughts below!
SigmaMind's MCP server exposes your entire voice AI stack as tools – agents, calls, campaigns, webhooks, phone numbers – manageable directly from your MCP client or IDE.
Spin up agents, trigger test calls, debug with inline call records, and automate deployments without leaving your editor.
Sub-800ms latency, SOTA noise cancellation, VAD, IVR navigation, and voicemail detection handled out of the box.
Hey everyone - wanted to share directly with our community first.
SigmaMind MCP Server goes live on Product Hunt at 12:01 AM EST Monday April 13 (12:31 PM IST).
It lets developers build and deploy voice AI agents directly from Cursor, Claude Code, VS Code, etc. - one natural language prompt, every setting configurable.
If you follow this page you'll get notified automatically when we go live. Would genuinely love your feedback on launch day: https://www.producthunt.com/prod...
SigmaMind AI (YC-backed) is a conversational AI platform to build voice and chat AI agents. Build with our no-code agent builder or plug in APIs. Prebuilt integrations + support for custom tools = fast, flexible deployment across industries.
