"Database connection and data query assistance" matching MCP servers:

Enables Claude AI to control Ableton Live and Max for Live, allowing music production tasks like track management, MIDI editing, and pattern generation directly from conversation.

Wallet-funded MCP client for six paid Utilia tools: Solana priority fees, transaction diagnosis and simulation, token-risk checks, PDF-to-Markdown, and audio normalization over x402. MIT-licensed and installable from npm.

Free Remotion video templates, creative guides and render diagnostics. No API key for local tools; optional paid hosted Studio workflows. Start with get_capabilities.

Provides tools to read PDFs, extract images, convert between PDF and DOCX, create DOCX from text, and generate PDFs from DOCX, text, or HTML.

Enables natural language control of Pure Data patches through Claude AI, allowing dynamic creation, modification, and DSP control via the Model Context Protocol.

Enables automated collection and downloading of multimedia content (images, GIFs, videos) from QQ channels. Features efficient video scraping, incremental updates, and intelligent fallback mechanisms for comprehensive media harvesting.

AI-native timeline editor for short-form video. Your agent cuts, captions, adds motion graphics and renders against a real, editable timeline over MCP — not a render queue. Human-in-the-loop by design: it calls request_review and waits while you supervise in a browser. Local-first and AGPL; your footage never leaves your machine.

Enables agentic interaction with vanilla Pure Data by providing tools for live patch creation, inspection, and manipulation via an MCP server that synchronizes with a Pd bridge patch.

A loopback-bound MCP server that enables MCP clients to control Ableton Live (set tempo, create tracks/clips, add MIDI notes, start/stop playback) over a secure local-only connection.

Enables AI assistants to control Ableton Live through MCP, allowing MIDI writing, audio import, device parameter adjustment, clip arrangement, and playback control over a localhost-only connection.

ModelRunner is a hosted remote MCP server that lets AI assistants run 100+ AI models. One connection exposes every model as a callable tool: search the catalog, inspect a model's input schema, run inference with run_model, and get results back as hosted URLs directly in the conversation.

Enables LLM routing through multiple providers (OpenAI, Anthropic, xAI) via LiteLLM and provides a bridge to Blender for 3D scene management, asset integration from PolyHaven/Sketchfab, and automation workflows. Combines unified text generation with comprehensive Blender integration through a persistent TCP connection.

A Cypher-style MCP server that enables AI agents to query and edit an Ableton Live Set via a property graph query language.

Provides tools to download YouTube videos and playlists asynchronously, with job tracking and metadata storage via a SQLite database, enabling library management through natural language.

A Model Context Protocol (MCP) server that connects AI coding assistants to DaVinci Resolve, enabling query and control through natural language.

Enables natural language control over Ableton Live for generating musical patterns, melodies, and full song arrangements. It also provides tools for sample searching and mixing assistance through an OSC-based connection with Claude Desktop.

A Model Context Protocol (MCP) server that learns from your video editing behavior and provides intelligent assistance for film and television post-production workflows.

A multimedia downloading and conversion MCP server supporting YouTube, HLS streams, podcasts, and images, with features like batch downloads, subtitle extraction, format query, and whitelist management.

Enables AI assistants to control and query Blender scenes through local MCP, allowing operations like retrieving scene information with objects and materials.

Enables agents to efficiently explore and query GStreamer debug logs by loading files, applying filters (path, category, time range, level, object name), and retrieving counts before fetching lines to keep context small.