"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP servers:

Model Context Protocol server for pyCycle/OpenMDAO engine-cycle workflows, enabling lifecycle management, variable inspection, execution, sweeps, and integration with CPACS aircraft analysis pipelines.

Enables AI agents to load, translate, simulate, and analyze Modelica models in Dymola via the Model Context Protocol.

Provides live astronomical telemetry and space data, including ISS tracking, NASA APOD, and solar weather, via a Model Context Protocol server with SSE and JSON-RPC support.

Provides seamless integration with NASA's public APIs, enabling AI assistants to access space and astronomy data including APOD, Mars rover photos, Near-Earth Objects, space weather events, and Earth imagery.

This MCP server enables AI agents to control kOS computers in Kerbal Space Program, providing tools for scripting, telemetry, and simulation management via telnet and file system integration.

Enables AI assistants to control and automate Abaqus/CAE simulations via MCP, including model query, job management, ODB inspection, KPI extraction, capsule tracking, physics contract validation, report generation, and viewport capture. It also supports noGUI batch mode, dual transport, and integration with Codex/Claude clients.

Enables an MCP client to drive CST Studio Suite 2026 through its official Python automation API, covering 3D modelling, materials, ports, boundaries, mesh and solver configuration, solver runs, and result reading. Also provides verification and export tools — S11, reference impedance, port diagnostics, energy budget and model audit — plus Touchstone/ASCII/JSON evidence output and parameter sweeps, all locally over stdio.

Enables interaction with SU2 CFD solver for session lifecycle management, config editing, solver execution, and results inspection, with optional CPACS integration for aircraft analysis.

MCP server for the INDIGO astronomy automation protocol, enabling AI agents to control telescopes, cameras, focusers, filter wheels, domes, and other observatory equipment through natural language.

SWMF MCP Server enables AI agents to work with the Space Weather Modeling Framework (SWMF) through tools for context, evidence, artifact inspection, and comparison. It includes task-specific skills for explanation, configuration, building, running, debugging, and analysis.