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 👋 We’re Ashish and Pratik, founders of SigmaMind AI.
After watching developers jump between dashboards, docs tabs, and their IDE just to configure a single voice agent - we knew the problem wasn't the technology. It was the workflow.
So we built SigmaMind MCP server.
Open Cursor, Claude Code, or VS Code. Type what you want:
"Build a customer support voice agent. GPT-4o. ElevenLabs, calm British female. Agent speaks first. Extract sentiment and escalation flags after every call."
That exact spec deploys. No dashboard opened. No context switching.
Here's what you're actually controlling from that one prompt: → LLM Model - GPT-4o, Claude, Gemini, or your own → Voice & TTS - pick the exact voice experience → Conversation Flow - who speaks first, how it behaves → Welcome Message - define the opening line → Background Audio - optional, on-brand → Post-Call Insights - sentiment, intent, escalation
Every layer configurable. All from natural language.
And telephony is built in - buy numbers or bring your own, assign to agents instantly, run real calls not simulations.
Under the hood: → Sub-800ms latency → IVR and phone trees navigation → Built-in VAD (Voice activity detection) → Noise cancellation for noisy background environments → Model-agnostic (Deepgram, GPT, ElevenLabs, or your own stack) → Multimodal (voice, chat, email - one agent brain) → Parallel tool calling for real-world actions
This looks super clean... managing everything from the IDE is a big win. Curious to try it out.
This is so cool. Running a VOICE AI company this is really good stuff. Congrats on the launch
i can direct claude code to an existing open source github repo and build voice agent for me with VAD / sub 800ms latency etc ? I understand this may consume more tokens. How is this MCP diff ?
MCP for voice agents makes sense. wiring voice into an agent stack always gets messy - nice that this abstracts it.
So proud of the team for getting the SigmaMind MCP Server live today!
I’ve seen how much effort went into making sure this wasn't just another 'cool tool' but a production-grade orchestration layer.
My favorite part? Being able to create and manage a Voice AI agent, all from a simple prompt, without leaving Cursor. It feels like magic every time.
We’re all hanging out here today to answer questions and get your feedback.
About SigmaMind MCP on Product Hunt
“Build and control voice AI agents via MCP”
SigmaMind MCP launched on Product Hunt on April 13th, 2026 and earned 119 upvotes and 13 comments, placing #10 on the daily leaderboard. 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.
SigmaMind MCP was featured in API (98k followers), Developer Tools (511k followers) and Artificial Intelligence (466.2k followers) on Product Hunt. Together, these topics include over 161.9k products, making this a competitive space to launch in.
Who hunted SigmaMind MCP?
SigmaMind MCP was hunted by Garry Tan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how SigmaMind MCP stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Garry Tan
Hey 👋
We’re Ashish and Pratik, founders of SigmaMind AI.
After watching developers jump between dashboards, docs tabs, and their IDE just to configure a single voice agent - we knew the problem wasn't the technology. It was the workflow.
So we built SigmaMind MCP server.
Open Cursor, Claude Code, or VS Code. Type what you want:
"Build a customer support voice agent. GPT-4o. ElevenLabs, calm British female. Agent speaks first. Extract sentiment and escalation flags after every call."
That exact spec deploys. No dashboard opened. No context switching.
Here's what you're actually controlling from that one prompt:
→ LLM Model - GPT-4o, Claude, Gemini, or your own
→ Voice & TTS - pick the exact voice experience
→ Conversation Flow - who speaks first, how it behaves
→ Welcome Message - define the opening line
→ Background Audio - optional, on-brand
→ Post-Call Insights - sentiment, intent, escalation
Every layer configurable. All from natural language.
And telephony is built in - buy numbers or bring your own, assign to agents instantly, run real calls not simulations.
Under the hood:
→ Sub-800ms latency
→ IVR and phone trees navigation
→ Built-in VAD (Voice activity detection)
→ Noise cancellation for noisy background environments
→ Model-agnostic (Deepgram, GPT, ElevenLabs, or your own stack)
→ Multimodal (voice, chat, email - one agent brain)
→ Parallel tool calling for real-world actions
Set up in under 5 minutes: https://docs.sigmamind.ai/mcp/se...