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

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

An MCP server that enables Claude Code and Claude Desktop to generate and edit images using OpenAI's gpt-image-2 model, with results saved to disk.

Generate and edit images with GPT Image 2.5 for $0.029 each, inside Claude, Cursor or any MCP client. A free you.bot API key comes with 50 credits (about 17 images) and needs no card.

Enables Codex to send text tasks to ChatGPT web, await responses, continue conversations, choose reasoning effort, and manage projects through MCP tools on macOS.

MCP server that pings 130+ free coding LLM models across 17 providers in real-time, ranks them by latency, and helps AI agents pick the fastest available model.

Trust, identity, and reputation infrastructure for AI agents. Register agents with W3C DID (Ed25519), check EigenTrust reputation scores, submit peer attestations, search agents by capability, and verify IPFS-anchored audit trails. 11 tools.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

An MCP server for image generation, editing, and analysis using OpenAI's gpt-image-1 model, with specialized templates for YouTube thumbnails, blog headers, social media, and more.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

Enables playing a Workato-themed text-based RPG through MCP tools, allowing users to explore dungeons, battle enemies, and manage character progression in an integration-themed adventure.

Enables AI assistants to directly manage Anki flashcards, decks, notetypes, tags, and media, with support for batch operations, searches, and deck exports via file-based input/output.

A comprehensive MCP server for managing AI-assisted Dungeons & Dragons campaigns, featuring tools for character sheets, combat tracking, and world-building. It enables players and DMs to interact with 5e game mechanics and query personal PDF rulebooks using RAG capabilities.

Wraps the gpt-researcher tool as an MCP server, enabling automated web research, information summarization, and structured report generation via natural language queries.

MCP sidecar for Hermes Agent exposing operator tools (cron, skills, config, workspace) with tiered read-only/operator/owner modes and dry-run by default for safe local development.

Standalone MCP server and CLI for generating images via ChatGPT backend, with reliable exact file paths and multi-account login support.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

Enables Claude Code to delegate web research and image generation to ChatGPT via Playwright browser automation, allowing token-efficient search and visual design iteration without manual screenshots.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.