"A server for improving AI math capability without using an API" matching MCP servers:

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.

Enables seamless integration with Typecast API through the Model Context Protocol, allowing clients to manage voices, convert text to speech, and play audio in a standardized way.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

An MCP server that integrates with fal.ai to provide AI agents with tools for image generation, text processing, audio synthesis, and model management via a unified interface.

Controls Ableton Live from an AI assistant with ~130 commands for tracks, instruments, effects, MIDI clips, automation, and mixing.

Enables AI agents and developers to generate images, videos, audio, and text using 100+ models via MCP or REST with a single API key.

Enables MCP clients to compose and render full songs locally using real sampled instruments, amp captures, AI vocals, and automated mixing/mastering, returning MP3/WAV/MIDI and stems.

Provides LLMs with full access to the Ken Video API for professional video processing, including adding audio, captions, and job management.

Enables AI agents to produce professional promo videos by providing tools for capture, media search, scene writing, rendering, editing, and incremental revision.

Enables AI agents to create and edit Strudel music code, render offline WAV audio, and obtain structured hearing reports with waveform, spectrogram, BPM, and onset analysis.

A low-latency text-to-speech MCP server that uses local Kokoro GGUF inference via TTS.cpp, providing say, get_voices, and get_status tools for AI agents to synthesize speech and manage playback queues.

Enables bounded, schema-validated automation of FMOD Studio game audio through MCP/CLI workflows, including inspection, safe mutations, previews, receipts, and high-level workflows for events, assets, parameters, adaptive music, spatial audio, banks, and mixer/routing.

Enables AI coding agents like Cline to analyze video, audio, PDFs, and images by sending files to OpenRouter's multimodal models. It also provides a CLI and Python module for media analysis, with support for time-range trimming, PDF OCR, and multiple models.

MCP server providing tools to fetch YouTube video transcripts with metadata, supporting direct YouTube transcripts and audio transcription via multiple backends (whisper, AssemblyAI, OpenAI, Gemini).

Enables AI assistants to programmatically edit, analyze, and export audio projects through MCP tools, including multi-track editing, effects, transcription, and semantic search.

MCP server for AI-powered media generation: images, videos, audio, and upscaling using 99 AI models.

Enables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.

Integrates AI-powered music generation with professional production tools, enabling autonomous music creation workflows from MIDI input to live streaming.

Enables AI assistants to read and control FL Studio 2025 projects via file-based RPC and MIDI wake, overcoming sandbox restrictions for tempo, mixer, and note recording.

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.