"DevOps tools and practices including CI/CD pipelines, GitOps, and DevSecOps" matching MCP servers:

Enables MCP clients to leverage the Intel Arrow Lake NPU for local speech transcription, screenshot OCR, private semantic search, and hardware diagnostics, all processed locally.

An MCP server enabling video processing via natural language: transcription with Whisper, segment cutting with FFmpeg, and file management.

An MCP server providing tools for speech-to-text, translation, language detection, question answering, and text-to-speech using Sarvam AI models, enabling multilingual voice agents.

Provides various AI capabilities through DeepInfra's OpenAI-compatible API including image generation, text processing, embeddings, speech recognition, object detection, and classification tasks. Enables users to access multiple AI models for diverse tasks like generating images from prompts, transcribing audio, analyzing text sentiment, and performing computer vision operations.

Provides AI tools with transcripts of any YouTube video, including videos without captions via AI speech-to-text, with language selection and length capping.

Enables provisioning and managing Vapi inbound answering assistants locally, including templates, phone numbers, tools, structured outputs, and test calls.

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 users to convert text into high-quality audio by accessing the OpenAI Text-to-Speech API. It supports customizable model selection and voice options for synthesized speech generation via the MCP protocol.

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 coding agents to build, test, and deploy production voice agents with real phone numbers directly from the editor, including live call monitoring and sandboxed development.

Provides multimodal understanding tools including OCR, image description, audio transcription, UI screenshot analysis, and screenshot comparison via async tools on a multimodal endpoint.

Enables AI agents to provision phone numbers, send SMS, place AI voice calls, and react to inbound events via the Dial communication stack, all through MCP tools.

Enables supported local AI clients to control a visible desktop presence through bounded presentation tools such as animations, window control, and short local speech over a loopback endpoint, without granting decision or execution authority.

Enables AI assistants to manage RetellAI voice services including calls, agents, phone numbers, and voices through natural language.

Enables MCP clients to place, monitor, and hang up phone calls through authenticated tools, retrieve transcripts, and exchange correlated task results with a waiting host. It supports simulated or live calling with persisted call lifecycle records, duration limits, and idempotent requests.

Enables AI agents to submit and manage durable long-form audio transcription jobs, and read or export structured transcripts via MCP tools.

Provides AI-powered media generation tools including image, speech, video, OCR, and voice conversion via the Model Context Protocol.

Enables agents to synthesize Chinese speech with Edge-TTS or offline Piper and generate engine-level timestamp SRT subtitles, including batch parallel synthesis and voice presets.

Give your AI agents the ability to listen. Microphone capture and speech-to-text tools for MCP-compatible agents.

Provides speech recognition and synthesis tools via SaluteSpeech API, enabling AI assistants to handle voice input and output.