Voice channel for any AI agent over MCP

What it looks like inside Claude Desktop

A real conversation: the user asks Claude to call a customer about tomorrow's appointment. Claude picks the make_call tool from the Stexa MCP server, sees the tool result, and reports back to the human.

Frame from a real Claude Desktop + Stexa Voice MCP session. Want a live demo? Sign up — sandbox DID is yours in a minute.

Compatible with any AI agent

Stexa Voice MCP is the JSON-RPC server side. The client can be any tool that speaks MCP. Three most common paths for developers and integrators.

{
  "mcpServers": {
    "stexa-voice": {
      "command": "npx",
      "args": ["-y", "@stexa-ai/mcp-client"],
      "env": {
        "STEXA_API_KEY": "sk_live_..."
      }
    }
  }
}

// agonts.workspace.ts
import { StexaVoiceMCP } from "@stexa-ai/agonts-plugin";

export const agent = defineAgent({
  name: "Sales bot",
  tools: [
    StexaVoiceMCP({
      apiKey: process.env.STEXA_API_KEY,
    }),
  ],
});

from langchain_mcp import MCPClientToolkit

toolkit = MCPClientToolkit(
    server_url="https://stexa.ru/mcp/v1/jsonrpc",
    bearer_token=os.environ["STEXA_API_KEY"],
)

agent = create_react_agent(llm, toolkit.get_tools())

Claude Desktop, AGONTS, Cursor are trademarks of their respective owners. Stexa AI is not affiliated and works through the open Model Context Protocol standard.

How it works

Stexa Voice MCP is one JSON-RPC endpoint that implements the MCP-2026 spec. No webhook servers on your side, no queues. Three steps from sign-up to your AI agent's first live call.

Full request example

Any JSON-aware HTTP client can talk to Stexa Voice MCP. Below — the anatomy of one make_call tool invocation with the full parameter set.

POST https://stexa.ru/mcp/v1/jsonrpc
Authorization: Bearer sk_live_a1b2c3d4...
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "id": 42,
  "method": "tools/call",
  "params": {
    "name": "make_call",
    "arguments": {
      "to": "+14155550123",
      "script": "Hi! Confirming your 2 PM appointment.",
      "voice": "alyona",
      "max_duration_sec": 60,
      "record": true,
      "callback_url": "https://example.com/webhooks/stexa"
    }
  }
}

// ↩ Response 200 OK (412 ms)
{
  "jsonrpc": "2.0",
  "id": 42,
  "result": {
    "content": [{
      "type": "text",
      "text": "{\"call_id\":\"call_01HXQ7P\",\"status\":\"dialing\",\"eta_seconds\":3}"
    }]
  }
}

Full tools reference (make_call, send_sms, schedule_callback, voice_outbound), error codes, and SDKs — on GitHub.

Tech specs

No vendor lock-in: open MCP standard, documented JSON-RPC, official catalog listings (Smithery + mcp.so). Transparent roadmap for OAuth and tool expansion.

Our place in the MCP ecosystem

9,400+

MCP servers in Smithery + mcp.so registries as of May 2026

97M

MCP client installs across the ecosystem (Claude Desktop, AGONTS, Cursor)

#1

voice MCP provider for Russian-language AI agents in ecosystem catalogs (May 2026)

Listed on Smithery Listed on mcp.so

Smithery registry mcp.so directory Claude Desktop AGONTS workspace

Sources: smithery.ai (registry statistics, May 2026), modelcontextprotocol.io. Ecosystem logos are trademarks of their respective owners, shown for informational purposes.

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