OpenAI is an AI research and deployment company dedicated to ensuring that artificial general intelligence benefits all of humanity.
Why this server?
Supports OpenAI Agents to access and utilize web data through the MCP server
Why this server?
Uses OpenAI to generate professional descriptions of projects and skills based on codebase analysis for enhancing JSON Resumes
Why this server?
Integrates with OpenAI Agents SDK, allowing OpenAI-based applications to manage and query Redis data through natural language commands.
Why this server?
Mentioned as a company that can be researched for funding information, including latest round size, valuation, and key investors.
Why this server?
Allows OpenAI Agents to use ElevenLabs' text-to-speech and audio processing features to generate and manipulate audio content.
Why this server?
Allows OpenAI Agents to use MiniMax's Text to Speech, voice cloning, and video/image generation capabilities
Why this server?
Provides compatibility with the OpenAI Agents SDK, allowing users to connect to the Atla MCP server for LLM evaluation services.
Why this server?
Utilizes OpenAI's gpt-image-1 model to generate image assets that can be used for game or web development
Why this server?
Allows sending chat messages to OpenAI's API and receiving responses from models like gpt-4o
Why this server?
Seamless integration with OpenAI models, enabling the use of OpenAI's AI capabilities with tools and prompts.
Why this server?
Provides a direct alternative to OpenAI Operator, allowing OpenAI models to interact with and control macOS systems through the MCP protocol.
Why this server?
Leverages OpenAI's embedding models for semantic search capabilities, supporting multiple models including text-embedding-3-small/large.
Why this server?
Integrates with Azure OpenAI API for batch analysis capabilities, enabling summarization, sentiment analysis, custom scoring, and research impact assessment on Smartsheet data.
Why this server?
Provides access to OpenAI services including chat completion, image generation, text-to-speech, speech-to-text, and embedding generation
Why this server?
Utilizes OpenAI's models for both text processing and embedding generation
Why this server?
Provides import capability for ChatGPT conversation history into the Basic Memory knowledge base.
Why this server?
Allows sending requests to OpenAI models like GPT-4o-mini via the MCP protocol
Why this server?
Integration with OpenAI's language models via their API for AI-driven browser automation
Why this server?
Provides access to OpenAI models like GPT-4o, with support for model switching and routing based on reasoning requirements.
Why this server?
Utilizes OpenAI GPT-4 Vision API for image analysis and detailed descriptions from both base64-encoded images and image files
Why this server?
Leverages OpenAI's capabilities to summarize video content and generate professional LinkedIn posts with customizable tone and style.
Why this server?
Leverages OpenAI's GPT-4o model through OpenRouter for vision-based image analysis tasks
Why this server?
Provides audio transcription capabilities using OpenAI's Speech-to-Text API, allowing conversion of audio files to text with options for language specification and saving transcriptions to files.
Why this server?
Supports using OpenAI's models for the ACT feature, allowing an agent to control a Scrapybara instance using natural language instructions.
Why this server?
Uses OpenAI's GPT-4o-mini model to generate commit messages based on code changes
Why this server?
Allows access to OpenAI models via the LLM_MODEL_PROVIDER environment variable and OPENAI_API_KEY
Why this server?
Allows querying OpenAI models (o3-mini and gpt-4o-mini) directly from Claude using the MCP protocol, enabling users to ask questions and receive responses from OpenAI's AI models
Why this server?
Potentially compatible with OpenAI's API for models that support tool/function calling capabilities
Why this server?
Utilizes OpenAI's GPT models for the architectural expertise provided by the MCP server
Why this server?
Creates OpenAI-compatible function definitions and tool implementations from Postman API collections, with proper error handling and response validation.
Why this server?
Provides OpenAI-compatible API endpoints for text completion
Why this server?
Supports GPT models from OpenAI as an AI provider for summarization capabilities
Why this server?
Leverages OpenAI's vision capabilities for AI-powered content extraction from media files (images and videos) when provided with an API key
Why this server?
Provides function calling service for OpenAI models to access cryptocurrency data from CoinGecko, including historical prices, market caps, volumes, and OHLC data
Why this server?
Integrates with OpenAI API for code analysis, providing detailed feedback, improvement suggestions, and best practices recommendations.
Why this server?
Supports OpenAI models (GPT-4, GPT-3.5) through compatible MCP clients, allowing AI-powered control of serial devices.
Why this server?
Uses OpenAI's API for embeddings generation to power the vector search capabilities of the RAG documentation system
Why this server?
Built-in support for accessing OpenAI models, allowing prompt execution and generation using GPT models.
Why this server?
Uses OpenAI API for AI functionality, requiring an API key for operation
Why this server?
Supports integration with OpenAI models via LiteLLM for large language model operations and generation tasks
Why this server?
Used internally for article summarization functionality, though this capability is not directly exposed via MCP prompts.
Why this server?
Supports OpenAI models for API generation, enabling the use of OpenAI's language models during the API configuration discovery process.
Why this server?
Integrates with OpenAI's models for language and vision capabilities, allowing the browser automation system to leverage OpenAI's AI models for processing and generating content.
Why this server?
Uses OpenAI's API to generate Stern's philosophical guidance and mentorship responses through the msg_stern tool.
Why this server?
Enables image generation capabilities using OpenAI's DALL-E 2 and DALL-E 3 APIs, with support for creating new images from text prompts, editing existing images, and generating variations of images.
Why this server?
Supports OpenAI as an LLM provider through API key integration
Why this server?
Supports use of OpenAI models like GPT-3.5-turbo for processing natural language queries to SQL databases, configurable through the server settings.
Why this server?
Provides access to OpenAI's models including GPT-4o and GPT-4o-mini through a unified interface for prompt processing.
Why this server?
Required for AI model access to power the investor agent simulations
Why this server?
Allows forwarding requests to an Brightsy AI agent using an OpenAI-compatible format, enabling interaction with the agent through a standardized messages array with role and content properties.
Why this server?
Supported as a model option for the text summarization feature
Why this server?
Utilizes GPT-4-turbo model to analyze and provide detailed descriptions of images from URLs
Why this server?
Enables integration with OpenAI's Assistant API, allowing AI assistants to use flight search, booking, and analysis capabilities through the Amadeus API.
Why this server?
Provides access to Deepseek reasoning content through OpenAI API
Why this server?
Leverages OpenAI capabilities for enhanced features in web search and content analysis, requiring an API key for AI-powered functionality.
Why this server?
Leverages OpenAI for analysis and report generation as part of the research workflow, processing collected information into structured knowledge
Why this server?
Provides compatibility with OpenAI API clients, serving as a drop-in replacement for standard OpenAI interfaces while implementing the Chain of Draft approach.
Why this server?
Supports using OpenAI embedding models for vectorizing content. Allows configuring namespaces to use various OpenAI embedding models like text-embedding-3-small and text-embedding-3-large.
Why this server?
Enables function calling with the Deriv API through OpenAI models, offering capabilities to fetch active trading symbols and account balances.
Why this server?
Offers an OpenAI-compatible chat completion API that serves as a drop-in replacement, enabling the use of local Ollama models with the familiar OpenAI chat interface and message structure.
Why this server?
Uses OpenAI's API for server functionality, with configuration for API key, base URL, and model selection (specifically gpt-4o-mini)
Why this server?
Generates images using OpenAI's DALL-E 3 model based on text prompts, saving the results to a specified location.
Why this server?
Enables seamless connection with OpenAI's services for advanced AI capabilities.
Why this server?
Supports token counting using OpenAI's tiktoken tokenizer with configurable encodings (e.g., o200k_base for GPT-4o, cl100k_base for GPT-4/3.5)
Why this server?
Uses OpenAI's embedding capabilities to generate vector embeddings for documentation chunks, enabling semantic searching of documentation content.
Why this server?
Integration with OpenAI models to create AI agents capable of performing Starknet blockchain operations.
Why this server?
Allows trading through OpenAI's GPT models using the HTTP server with Open WebUI integration
Why this server?
Allows sending requests to OpenAI models like gpt-4o-mini using the Unichat MCP server
Why this server?
Compatible with OpenAI-compliant LLMs to power test discovery, crawl websites, and suggest test steps for discovered pages.
Why this server?
Compatible with OpenAI-compliant LLM APIs for AI-powered test discovery and execution, allowing any OpenAI-format LLM to power the testing capabilities.
Why this server?
Uses OpenAI API for generating vector embeddings for crawled content to enable semantic search
Why this server?
Leverages OpenAI's LLM capabilities for inference operations and embeddings within the knowledge graph framework
Why this server?
Allows custom GPT models to communicate with the user's shell via a relay server
Why this server?
Expected future integration with ChatGPT (mentioned as coming soon), which would allow using the MCP server with OpenAI's models
Why this server?
Integrates with OpenAI's API for automated end-to-end testing, requiring an OpenAI API key to run the MCP server in end-to-end mode for LLM-driven test validation.
Why this server?
Enables management of Azure OpenAI resources, including checking rate limits of deployed models and other configurations
Why this server?
Allows ChatGPT to utilize GraphQL operations as tools through OpenAI's function calling capability, enabling interaction with any GraphQL API.
Why this server?
Provides integration with OpenAI's API, allowing OpenAI models to access and use tools exposed by the MCP server for retrieving information like knowledge base data.
Why this server?
Integrates with OpenAI models like GPT-4o for LLM-based data quality assessment using various evaluation prompts
Why this server?
Enables image generation and editing using OpenAI's gpt-image-1 model, providing tools to create images from text prompts, edit existing images, and perform inpainting with masks.
Why this server?
Enables OpenAI Agents to access lyrics, song, and background music generation capabilities through the Mureka API.
Why this server?
Provides tools for generating and editing images using OpenAI's GPT-4o/gpt-image-1 APIs, supporting text-to-image generation, image editing operations (inpainting, outpainting, compositing), and advanced prompt control.
Why this server?
Uses OpenAI's API to power the browser automation capabilities, requiring an API key for operation
Why this server?
Enables the use of cloud-based LLMs via OpenAI's API as an alternative to local models, providing flexibility in model selection.
Why this server?
Leverages Azure OpenAI for semantic code search capabilities, finding code based on meaning rather than exact text matches.
Why this server?
Provides integration with OpenAI's API for LLM services, supporting models like GPT-4o.
Why this server?
Connects with OpenAI models to process API definitions and interact with Swagger-documented endpoints.
Why this server?
Integrates with OpenAI API to provide text completion and chat functionality via dedicated endpoints
Why this server?
Leverages OpenAI's API for agent capabilities, requiring an API key for authentication
Why this server?
Enables access to OpenAI's Web Search capabilities through both Chat Completions API and Responses API, allowing AI models to search the web for current information with customizable geographic context and citation handling.
Why this server?
Integration with OpenAI is mentioned as a pending implementation under Bot Integrations.
Why this server?
Allows OpenAI Agents to interact with DiceDB databases through tools for basic database operations including ping, echo, get, set, delete, increment, and decrement functions.
Why this server?
Uses OpenAI's embedding models and LLMs for memory management, with configurable model selection through environment variables.
Why this server?
Serves as the default LLM evaluator for the MCP security gateway, validating prompts against Nova security patterns
Why this server?
Supports converting OpenAPI specs to OpenAI tools format for integration with OpenAI models
Why this server?
Enables connection to OpenAI's language models for AI-powered chat and assistant capabilities
Why this server?
Provides access to OpenAI's models such as GPT-3.5, GPT-4o, and GPT-4o mini for cost-effective task delegation and processing.
Why this server?
Provides LLM provider integration for task analysis, complexity estimation, and generating task file templates using OpenAI models like GPT-4
Why this server?
Referenced indirectly through MCP-Bridge which maps MCP tools to OpenAI's format, suggesting compatibility with OpenAI models.
Why this server?
Enables compatibility with OpenAI API standards when ENABLE_OPEN_AI_COMP_API option is enabled, allowing clients to interact with the privateGPT server using OpenAI-compatible API calls.
Why this server?
Processes real-time call audio using OpenAI's realtime model to enable natural voice conversations and responds with generated voice streams
Why this server?
Enables AI agents to utilize OpenAI's models for generating embeddings and providing language model capabilities for memory operations
Why this server?
Supports integration with OpenAI Agents Python SDK, enabling OpenAI models to leverage WhatsApp functionality through the MCP interface.
Why this server?
Referenced as a required integration with API key setup, and mentioned in code structure as a provider integration for the chat system.
Why this server?
Integrates with Azure OpenAI to provide AI model capabilities. The server implements a bridge that converts MCP responses to the OpenAI function calling format.
Why this server?
Integrates with OpenAI's API to provide LLM capabilities that can be queried through the MCP server, allowing for tools like weather information retrieval to be called via the client interface.
Why this server?
Used for generating zod schemas from Wordware flow information in the add-tool utility
Why this server?
Leverages OpenAI GPT models to summarize video transcripts and generate professional LinkedIn post content with customizable tone, voice, and audience targeting.
Why this server?
Integrates with Azure OpenAI services for text embeddings and the AI Assistant functionality that helps users find products and retrieve order information
Why this server?
Integrates with OpenAI's API for powering the research functionality, requiring an API key for operation.
Why this server?
Powers the RAG query functionality, enabling the retrieval of relevant information from indexed documents.
Why this server?
Supports OpenAI LLMs for executing MCP server tools through the LangChain ReAct Agent.
Why this server?
Enables integration with OpenAI models (like GPT-4) for agent conversations, with configurable LLM settings including model selection and temperature
Why this server?
Provides access to OpenAI's GPT models through a standardized interface, supporting customizable parameters like temperature and max tokens
Why this server?
Enables vector embeddings generation using OpenAI's embedding models for document indexing and semantic search capabilities.
Why this server?
Provides LLM capabilities for the prompt enhancement engine, including content classification and parameter extraction
Why this server?
Utilizes OpenAI platform API keys for certain functionalities within the MCP server
Why this server?
Leverages OpenAI's TTS API to convert text to high-quality speech with multiple voice options, models, and output formats
Why this server?
Provides access to locally running LLM models via LM Studio's OpenAI-compatible API endpoints, enabling text generation with custom parameters like temperature and token limits.
Why this server?
References accessing OpenAI API keys stored in environment variables, highlighting the potential security risk of exposing these credentials
Why this server?
Leverages OpenAI's embedding capabilities for processing and semantically searching documents in Qdrant collections.
Why this server?
The MCP server integrates with OpenAI as an LLM provider, allowing AI applications to interact with Crawlab through the MCP protocol. The architecture shows OpenAI as one of the supported LLM providers for processing natural language queries.
Why this server?
Utilizes OpenAI API for functionality, likely for embedding generation to support vector search operations with the Weaviate database.
Why this server?
Utilizes GPT-3.5-turbo model to generate dynamic interrogation strategies, simulate suspect responses, and create realistic dialogue flows for police interrogation simulations.
Why this server?
Uses OpenAI embeddings for vector search capabilities, requiring an API key for generating embeddings of documentation content
Why this server?
Supports integration with OpenAI models (like ChatGPT) as AI agents that can perform DeFi operations on Solana through the MCP server.
Why this server?
Provides access to OpenAI's websearch tool to query for current information from the web
Why this server?
Supports using OpenAI models with Aider's file editing capabilities by allowing configuration of OpenAI API keys.
Why this server?
Wraps OpenAI's built-in tools (web search, code interpreter, web browser, file management) as MCP servers, making them available to other MCP-compatible models.
Why this server?
Integrates with OpenAI's API for LLM functionality, enabling AI-powered browser control with customizable parameters
Why this server?
Enables text generation using OpenAI models through Pollinations.ai's API service
Why this server?
Provides integration with OpenAI's API, likely for embeddings or other AI capabilities when working with Weaviate
Why this server?
Uses OpenAI API for advanced reasoning LLMs to generate plans and instructions for coding agents, and powers the Code Architect tool
Why this server?
Enables testing prompts with OpenAI models, allowing configuration of system prompts, user prompts, and parameters like temperature and max_tokens
Why this server?
Uses OpenAI's Whisper model for audio transcription, enabling conversion of recorded voice to text with different model sizes for varying accuracy and performance needs
Why this server?
Can use OpenAI's embedding models as an alternative to Ollama for creating vector embeddings for documentation search
Why this server?
Uses the OpenAI API for LLMs to power coding assistance features
Why this server?
Supports importing and analyzing OpenAI chat exports through the 'openai_native' format option.
Why this server?
Provides paid embeddings for vector representation of documents as an alternative to Ollama
Why this server?
Allows creating and interacting with OpenAI assistants through the Model Context Protocol (MCP). Enables sending messages to OpenAI assistants and receiving responses, creating new assistants with specific instructions, listing existing assistants, modifying assistants, and managing conversation threads.
Why this server?
Provides seamless access to OpenAI's models (gpt-4o, gpt-4o-mini, o1-preview, o1-mini) directly from Claude, allowing users to send messages to OpenAI's chat completion API with the specified model.
Why this server?
Allows querying OpenAI models directly from Claude using MCP protocol
Why this server?
Leverages GPT-4 for task planning and code generation, enabling AI-powered analysis and creation of code based on specified tasks
Why this server?
Provides an example implementation for integrating OpenAI models within the handle_sample method, allowing developers to use GPT-4 for processing prompts and generating responses.
Why this server?
Uses OpenAI embeddings API for document indexing and semantic search, enabling efficient information retrieval from documentation databases
Why this server?
Integrates with OpenAI API for generating completions, enabling RAG capabilities with various models including GPT-4.
Why this server?
Offers compatibility with OpenAI API standards, enabling integration with OpenWebUI and other LLM interfaces that use the OpenAI API format
Why this server?
Integrates with OpenAI's API for LLM capabilities, using API keys to access models for text generation and processing.
Why this server?
Connects to an image system that selects and displays images from the server/openai-server/public/image directory on the virtual TV
Why this server?
Uses OpenAI's Whisper model for high-quality multi-language audio-to-text transcription
Why this server?
Uses OpenAI GPT models to generate and execute SQL queries based on natural language questions, then summarizes results in structured format.
Why this server?
Allows interaction with OpenAI models (specifically GPT-4o) to ask questions and receive AI assistance
Why this server?
Integrates with Azure OpenAI for advanced functionality related to search and content processing.
Why this server?
Used in examples for storing API keys, specifically referencing OpenAI API keys that can be securely stored and retrieved
Why this server?
Integrates with OpenAI's API for AI model access, supporting function calls and processing natural language requests from Lark messages
Why this server?
Used for generating embeddings for the hybrid search functionality, powering semantic search capabilities for Teams messages.
Why this server?
Leverages the OpenAI Agents SDK to create intelligent agents capable of understanding and executing user prompts for AWS resource management tasks.
Why this server?
Integrates with OpenAI's API for model generation capabilities, enabling use of models like GPT-4 for retrieval-augmented generation tasks
Why this server?
Uses OpenAI's API for generating embeddings to power the semantic search functionality over PyTorch documentation
Why this server?
Supported AI provider for the MCP server, allowing connection to OpenAI API with models like GPT-4o.
Why this server?
Exposes OpenAI agents through the MCP protocol, including specialized agents for web search, file search, and computer actions, plus a multi-agent orchestrator
Why this server?
Uses OpenAI's API for resume and cover letter generation capabilities, as indicated by the configuration requirement for an OpenAI API key.
Why this server?
Optional integration mentioned as a possible API connection, though specific capabilities aren't detailed
Why this server?
Integrates Paybyrd's payment processing API with OpenAI models through function calling, allowing creation of payment links, processing refunds, and retrieving order information.
Why this server?
Integrates with OpenAI API to provide deep thinking and analysis capabilities, supporting multiple AI models including o3-mini and gpt-4 for problem solving, code enhancement, and code review.
Why this server?
Provides access to OpenAI's ChatGPT API with customizable parameters, conversation state management through the Responses API, and web search capabilities for retrieving up-to-date information.
Why this server?
Integrates with OpenAI models like GPT-4 to power the AI agent capabilities for recruitment tools and data analysis tasks
Why this server?
Integrates with OpenAI to process weather queries, requiring an API key for authentication to access weather information services.
Why this server?
Enables integration with OpenAI models for the RAG (Retrieval-Augmented Generation) pipeline, allowing enhanced responses based on retrieved information from the vector database.
Why this server?
Leverages OpenAI models (gpt-4o-search-preview and gpt-4o-mini-search-preview) as research agents for conducting information searches and analysis.
Why this server?
Enables routing requests to OpenAI's models through the MCP server, providing access to OpenAI's AI capabilities via a unified proxy interface
Why this server?
Provides access to OpenAI's official documentation, enabling users to search and retrieve relevant documentation content through the get_docs tool.
Why this server?
Provides an OpenAI-compatible interface through the /openai/v1/{agent_id}/chat/completions endpoint, allowing agents to be accessed via OpenAI SDK clients.
Why this server?
Generates vector embeddings using OpenAI's embedding models to create searchable vectors from project data that are stored in Supabase.
Why this server?
Integrates with OpenAI's Computer Use API to interpret and execute natural language instructions for browser automation, supporting a wide range of actions like clicking, typing, and scrolling.
Why this server?
Allows fetching and searching of current OpenAI documentation, providing access to the most recent API references and guides.
Why this server?
Connects to OpenAI's API to analyze code and perform detailed code reviews, with support for models like gpt-4o and gpt-4-turbo to identify issues and provide recommendations.
Why this server?
Provides semantic search capabilities using OpenAI embeddings to convert text into vector representations for search queries
Why this server?
Provides web search capabilities through OpenAI's 4o-mini Search model, allowing users to retrieve up-to-date information from the web
Why this server?
Leverages OpenAI models to power the natural language interface for querying and interacting with MLflow data
Why this server?
Provides access to OpenAI documentation for reference and assistance with API usage
Why this server?
Leverages OpenAI models to power the role-based AI responses, with configurable model selection and API key integration.
Why this server?
Uses faster-whisper, a faster implementation of OpenAI's Whisper model, for local speech-to-text conversion
Why this server?
Uses OpenAI's API for vectorizing documents to create embeddings for the knowledge base, requiring an API key for operation.
Why this server?
Provides tools for generating, editing, and creating variations of images using OpenAI's DALL-E models, supporting both DALL-E 2 and DALL-E 3 with various customization options for image size, quality, and style.
Why this server?
Compatible with OpenAI models through the 5ire client, allowing them to interact with and control DaVinci Resolve features.
Why this server?
Provides text generation capabilities using OpenAI's GPT-4 model through the gpt4_completion tool.
Why this server?
Integration with OpenAI's API for access to GPT models like gpt-4o.
Why this server?
Integrates with OpenAI's API for content generation and tool usage, while also providing access to OpenAI Agents SDK documentation
Why this server?
Leverages OpenAI's Agents SDK to expose individual specialized agents (Web Search, File Search, Computer Action) and a multi-agent orchestrator through the MCP protocol.
Why this server?
Uses OpenAI API to power the browser automation capabilities, with an API key being required in the .env file
Why this server?
Uses OpenAI's embedding models for semantic search of stored memories and connects with OpenAI-compatible AI assistants
Why this server?
Enables interaction with OpenAI's models (GPT-4o-mini and O3-mini) through the DuckDuckGo AI chat tool.
Why this server?
The README shows configuration with an OPENAI_API_KEY in the .env file, suggesting integration capabilities with OpenAI's services.
Why this server?
Uses OpenAI's Triton language for custom CUDA kernels that optimize model performance.
Why this server?
Used for content generation, allowing the MCP server to create social media posts using OpenAI's models
Why this server?
Utilizes OpenAI's GPT models to provide real-time code review, analysis, and improvement suggestions within Cursor IDE
Why this server?
Leverages OpenAI's GPT models to interpret natural language commands for browser automation tasks
Why this server?
Integrates with OpenAI API for providing intelligent code suggestions and reducing hallucinations
Why this server?
Provides specialized tools for testing OpenAI's GPT models and generating images with DALL-E without sharing API keys in the chat, including chat completions and image generation capabilities.