"Ionic" matching MCP servers:

Provides AI assistants with current Ionic Framework v9 and v8 documentation, including component API references, usage examples for Angular, React, Vue, and vanilla JavaScript, and Ionic blog posts. Enables searching docs, reading pages, listing components, retrieving usage examples, and listing blog posts.

Gives AI assistants access to current Capacitor documentation, plugin listings, and Ionic blog posts so they can provide accurate answers about Capacitor APIs and CLI usage.

MCP server that connects Claude Code to Sonic Pi for AI-assisted beat making, enabling live code execution and pattern management.

An MCP server for HF radio propagation analytics using the IONIS dataset collection, enabling natural language queries about band conditions, propagation paths, and solar correlations.

Enables video-aware background music recommendations by analyzing local videos or URLs for mood, pace, speech, and scene cuts, then returning license-safe, ranked tracks with beat/cut hints and preview mixes.

Enables AI agents to manage events, venues, songs, and users via the Sonic API, with integrated Spotify and Google Maps search.

Enables control of a local Sonic Pi runtime to run code, stop jobs, read events, and search docs/samples/synthdefs via OSC messages.

A Model Context Protocol server that allows AI assistants like Claude and Cursor to create music and control Sonic Pi programmatically through OSC messages.

Encodes a TypeScript/JavaScript codebase into a deterministic PNG heatmap that vision-capable AI models can read to bypass token limits for codebase-scale audits.

just a test of glama

Enables interaction with the Sonic blockchain including wallet management, token transfers, staking, and bridging between Ethereum and Sonic networks.

Bridges LM Studio local models to Claude Code as MCP tools, enabling private and free AI-assisted subtasks. Includes respond and models tools with automatic model selection and structured output.

Enables local, private analysis of YouTube URLs and local audio files to extract BPM, key modulations, vocal presence, transient punch, stereo width, and CLAP vibe embeddings, returning structured sonic signatures for AI agents and CLI users.

Enables agents to analyze video footage or URLs and return ranked, license-safe BGM matches with hook windows, beat/cut hints, and ffmpeg ducking or mix specs. It also supports batch mood clustering, brand kits, preview beds, and attribution-aware exports without shipping raw video payloads.

Enables agents to ingest a local clip or URL, analyze its scenes, mood, pace and speech, and receive ranked license-safe BGM recommendations with a 12–20s hook window, beat-snapped cut suggestions, mix previews, and ffmpeg ducking specs. Every recommendation carries its license and attribution text, and optional user-owned catalogs or API-backed analysis can be layered in.

Enables agents to analyze video footage and receive license-safe background music shortlists with printed license and attribution details, plus a 12–20s hook window, beat-snapped cut suggestions, and ffmpeg ducking/mix specs. It works from a local file or URL and can preview a mix or export the spec without pushing raw video through the payload.

Enables agents to ingest video, analyze mood, pace, speech, and scenes, and return ranked license-safe BGM matches with license and attribution details. It also provides 12–20s hook windows, beat-synced cut suggestions, and ffmpeg ducking or mix specs for editing workflows.

Enables agents to ingest and analyze video footage for mood, pace, speech, and scenes, then returns license-safe BGM matches, hook windows, cut suggestions, and ffmpeg ducking/mix specs. It supports offline seed catalogs and optional licensed libraries while printing each track's license and attribution.

Enables agents to ingest local or hosted video clips, analyze footage mood, energy, speech, and scene cuts, and receive license-safe BGM shortlists with per-track licensing, a 12–20s hook window, and an ffmpeg ducking/mix spec. It also supports beat-snapped cut suggestions, brand kits, batch mood clustering, and mix previews or rendered previews without shipping raw video bytes.

Enables agents to ingest video or public URLs, analyze footage for mood, energy, speech, and scenes, and return license-safe BGM recommendations with hook windows, cut suggestions, and ffmpeg ducking/mix specs.