OpenAI를 위해 구축된 459개의 MCP를 찾아보세요.
Converts text to speech using OpenAI's API from the command line.
Provides a beginner-friendly guide to creating self-operating AI agents using Python, the OpenAI API, and ReAct prompts.
Provides a unified interface for text-to-speech engines, including Kokoro TTS and OpenAI TTS.
Integrates AI-powered code generation, review, refactoring, and translation capabilities into Sublime Text, connecting to a local Model Context Protocol server.
Facilitates code review and implementation planning using large language models by providing them with extensive code context.
Provides unified access to over 100 AI providers, including OpenAI and Anthropic, through a single, consistent interface.
Provides voice status updates using OpenAI's text-to-speech API.
Analyzes the content of images from provided URLs using the GPT-4-turbo model.
Synthesizes text into speech and plays it locally using the OpenAI TTS SDK.
Converts Claude API requests into OpenAI API format using a Cloudflare Workers proxy, enabling seamless integration with OpenAI-compatible clients.
Provides deep thinking capabilities to Claude Desktop using OpenAI's o3-mini model and the Model Context Protocol.
Provides a high-performance, embedded MCP server for semantic code search, integrating keyword and vector-based analysis.
Provides a unified CLI for real-time network telemetry querying, connectivity analytics, and AI-powered insights, leveraging MCP server capabilities.
Leverages AI to categorize, tag, and enhance educational course content.
Demonstrates the use of a Model Context Protocol (MCP) server with various agent frameworks like Google ADK, LangGraph, OpenAI Agents, and Pydantic-AI.
Builds a RAG-based HR chatbot that provides workplace rules using a localhost MCP server.
Provides a scriptable desktop chat application for interacting with various Large Language Models (LLMs).
Provides an MCP server for using the Garak LLM vulnerability scanner.
Provides a web-based interface for interacting with Large Language Models (LLMs) and managing context aggregation.
Enables natural language interaction with multiple service backends using the Modular Capability Protocol (MCP).
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