"Connecting Feishu (Lark)" matching MCP servers:

Enables AI agents to manage phone numbers, send/receive SMS, and place voice calls through natural language, connecting to the phone network via the AgentPhone API.

Enables agents to analyze speech prosody and vocal sentiment, including speech rate, pitch variance, and cognitive fatigue, to dynamically calibrate response pacing.

Enables real-time voice agents to dynamically modulate speech pitch, cadence, and pause inflections via prosody, SSML, and emotion pacing for low-latency conversational audio.

An MCP server that estimates acoustic noise floors and applies spectral gating to suppress ambient reverberation in real-time voice audio. It enables developers and AI agents to run deterministic, zero-dependency noise suppression through any MCP-compliant client.

Enables real-time voice activity detection, dynamic silence endpointing, and barge-in interruption for conversational voice agents.

Enables real-time voice agents and streaming audio pipelines to detect conversational turn completion, distinguishing finished speech turns from mid-sentence hesitation pauses using acoustic VAD and semantic scoring. It provides low-latency decision and telemetry output through a native MCP interface for integration with MCP-compliant clients.

Enables real-time voice agents and streaming pipelines to smooth audio playout over volatile network conditions by providing adaptive jitter buffering and packet loss concealment. It exposes an MCP-compliant server that accepts audio frames and telemetry, returning low-latency decision and diagnostic output.

Enables deterministic psychoacoustic modeling of dichotic hearing thresholds, interaural phase differences, brainstem processing scores, and cocktail-party speech-in-noise intelligibility through JSON-RPC tools.

Enables autonomous agents to orchestrate HubX mobile AI tools for plant and nutrition vision diagnostics, voice transcription and summarization, photo-realistic portrait and art generation, and interior/exterior spatial design through structured JSON outputs.

Enables real-time full-duplex voice agents to classify user interruptions, backchannels, and acoustic echo, and to arbitrate turn-taking with context rollback via MCP.

Exposes an MCP tool that fuses acoustic prosody measurements (F0, speaking rate, jitter, pause ratio) with semantic sentiment to infer high-dimensional emotional states from speech. Returns tone, speaking-rate multiplier, and pitch-shift directives so agents can drive real-time expressive TTS modulation through JSON-RPC over stdio.

Enables sub-100ms conversational turn-taking and barge-in handling for voice agents, integrating with Cartesia Sonic and ElevenLabs, and can be used by MCP-compliant clients like Claude Desktop and Cursor.

Enables analysis of acoustic vocal emotion, prosodic valence, and customer frustration from audio inputs through a zero-dependency MCP server.