"Information about Python programming or Python-related topics" matching MCP servers:

Enables AI assistants to perform video and audio processing tasks such as format conversion, cutting, merging, and adding effects via FFmpeg, with hardware acceleration support.

Enables detection of AI-generated content in images, videos, audio, and text via the AI or Not API. Supports media analysis tools for deepfakes, synthetic voices, and AI-written text.

MCP server for audio transcription using OpenRouter models, supporting verbatim, cleaned, and custom transcription modes.

A Windows-native MCP server that lets Claude Desktop transcribe audio files locally using whisper.cpp, with no internet connection required.

Enables an MCP client to inspect and modify a running digital audio workstation session through a local Python remote-script TCP bridge, exposing tools for session and track structure, clip slots and MIDI notes, devices and browser items, and mixer/transport control. Read and bulk-write operations cover tempo, naming, clip creation and note editing, muting/soloing/arming, playback and scene launching, and device parameter loading and adjustment.

An MCP server for OBS Studio that subscribes to events and maintains a history, enabling queries about audio levels, source states, and past actions rather than only one-shot requests.

Provides local-first audio/video analysis by downloading media, transcribing it, and returning structured labels for topics, sentiment, sensitivity flags, and a publish/review/block gate.

Enables access to a backend's native MCP tools and broader HTTP API for speech generation, voice cloning/design, transcription, dubbing, translation, subtitles, audiobooks, and related batch/long-form workflows over Streamable HTTP or local stdio.

An official Model Context Protocol (MCP) server that enables AI clients to interact with ElevenLabs' Text to Speech and audio processing APIs, allowing for speech generation, voice cloning, audio transcription, and other audio-related tasks.

An MCP server that enables users to control and edit REAPER projects through a Python-based interface and a Lua bridge. It supports managing tracks, controlling transport, manipulating MIDI and audio items, and adjusting FX parameters within the digital audio workstation.

An MCP server that enables AI assistants to search, analyze, and retrieve information about audio samples from Freesound.org through their API.

A powerful MCP tool for parsing and manipulating MIDI files that allows users to read, analyze, and modify MIDI files through natural language commands, supporting operations like reading file information, modifying tracks, adding notes, and setting tempo.

An MCP server for parsing and analyzing Ableton Live .als project files offline, enabling queries about tempo, tracks, clips, and MIDI data through tools like als_summary and als_list_tracks.

Local Python MCP server for inspecting and automating Ableton Live Sets, including MIDI editing, device control, audio analysis and groove tools. Connects MCP clients to a MIDI Remote Script and extension bridge on the user’s machine.

Enables searching and downloading audio samples from Freesound using keywords, filters, and sound IDs. It provides detailed sound metadata including duration, license information, and preview URLs.

Enables AI agents to control Ableton Live by evaluating arbitrary Python code and using predefined tools for common tasks, supporting voice and text commands for music production.

Enables configuring Morningstar MIDI foot controllers using natural language, including switch mapping, MIDI CC lookup, conflict detection, and USB programming.

A Model Context Protocol server that integrates with VOICEVOX engine to provide text-to-speech synthesis and speaker information retrieval, allowing users to generate and play voice audio from text.

Enables AI clients to transcribe YouTube links and uploaded audio or video files, then retrieve the resulting transcripts as text, SRT, VTT, or JSON with timestamps and optional speaker labels. Also supports paging through long transcripts, checking upload progress, listing or deleting jobs, and viewing remaining account minutes.

Enables AI agents to fuse 2D/3D visual bounding boxes, user head-pose gaze vectors, and acoustic beamforming azimuth angles into cross-modal focal salience scores. It also resolves deictic spatial references in real time, running as a zero-dependency Python MCP server over JSON-RPC stdio.