"A tool for generating and live previewing Mermaid diagrams from code" matching MCP servers:

A Model Context Protocol (MCP) server that converts Mermaid diagrams to PNG images.

Enables AI agents to operate a real-time DJ rig inside Ableton Live, controlling two decks, bar-quantized firing, crossfades, performance FX macros, and a harmonic crate that suggests next tracks by BPM and Camelot key.

A local MCP server for Cursor that converts Markdown files and Mermaid diagrams to JPEG images with configurable dimensions and quality.

Enables AI assistants to inspect and edit an Ableton Live set in real time, including tracks, devices, parameters, clips, MIDI, and undo-safe changes, with guardrails such as all-or-nothing validation and optional read-only mode.

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

Enables MCP clients to control Ableton Live through a Max for Live device and optional Remote Script, covering tracks, clips, MIDI notes, mixer settings, transport, and plugin search and insertion.

An MCP server that converts Markdown files containing Mermaid diagrams into PDF documents by rendering diagrams as SVG images. It provides a specialized tool to automate document conversion while ensuring all visual charts are correctly embedded in the final output.

Local MCP server for inspecting and controlling Ableton Live through a local HTTP bridge. Enables LLMs to perform production workflows like MIDI import, track editing, mixing, mastering, and export.

Enables MCP clients to programmatically control an Ableton Live 12 session, including tracks, clips, MIDI notes, devices, parameters, mixer, scenes, warping, and rendering, over streamable HTTP.

Enables LLMs to control Ableton Live via OSC and the Model Context Protocol, supporting commands like setting up tracks and routing.

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.

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 generating beautiful syntax-highlighted code screenshots with professional themes directly from Claude. Supports file reading, line selection, git diff visualization, and batch processing across 20+ programming languages.

Enables LLMs to control Ableton Live digital audio workstation through OSC (Open Sound Control) protocol. Provides comprehensive tools for managing tracks, routing, and DAW configuration through natural language commands.

Enables AI agents to manage Tencent Cloud Live services through natural language, including domain management, stream pulling/pushing, live stream control, and transcoding template operations.

Enables Claude or any AI agent to operate Live 12 Intro end to end: creating tracks and scenes, writing and quantizing MIDI clips, loading audio onto the Arrangement timeline, setting device parameters in real units, drawing clip automation, mixing with real sidechain, and rendering or analyzing audio so the agent can check its own work. It exposes 57 tools over MCP or a local JSON socket, working within the stock Intro edition's 16-track, 16-scene limits.

Enables AI agents to control Ableton Live with full access to Live's object model, including clip creation, device control, automation, and audio signal capture for mixing and mastering tasks.

Enables Claude Code to use Alibaba Cloud Token Plan models via a local proxy that maps Anthropic-style model names to Alibaba IDs and provides missing endpoints like model discovery.

AI-powered music production toolkit enabling AI agents to generate, remix, separate stems, master tracks, and control DAWs via MCP.

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.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

Enables AI assistants to inspect and organize Adobe Premiere Pro projects, edit timelines with frame-accurate cuts and trims, animate motion and opacity keyframes, and trigger exports through natural language.

Enables AI assistants to programmatically inspect projects, create compositions and layers, apply effects, animate properties, and manage render jobs in Adobe After Effects through natural language.

Windows-optimized MCP server that enables control of Blender 4.0+ through 21+ tools for scene management, object manipulation, and asset downloads from PolyHaven, Sketchfab, Hyper3D, and Hunyuan3D.

Enables AI agents to control and inspect Ableton Live by executing Python code directly against the Live Object Model. It allows for automated track management, MIDI note creation, and real-time session manipulation through a natural language interface.

Control Ableton Live using natural language via Claude Code, with music theory engine for progressions, project persistence, and song cloning.

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.

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.

An MCP server that enables AI assistants to control Ableton Live, providing 104 tools for music production including track, clip, device, and mixer control.

Enables AI agents to perceive and quantitatively verify physical hardware through USB webcams and RTSP/HTTP network streams, returning inline image content plus numerical metrics such as brightness, contrast, edge density, motion, SSIM baseline comparisons, and OCR text. Agents can watch feeds for visual conditions, correlate buffered frames with serial/log/MQTT events, and apply privacy masks and access controls.