Discover 372 MCPs built for OpenAI.
Provides a web interface to interact with Multiple Control Protocol (MCP) servers while leveraging OpenAI's API for message processing.
Provides intelligent code context and analysis for modern IDEs by leveraging semantic analysis, AST parsing, and token-efficient compression for AI assistants.
Orchestrates scalable LLM function and tool calls with dynamic planning, memory lifecycle hooks, and parallel execution for production AI agents.
Provides a comprehensive Model Context Protocol (MCP) server application demo built with Windows Forms, integrating LLM API calls, a modern chat interface, and tool management.
Provides AI-powered answers to weather queries by integrating real-time data with natural language processing capabilities.
Enhances and cleans raw prompts using AI, improving clarity, actionability, and effectiveness.
Provides a basic server implementation for use with the MCP CLI.
Extracts key-value pairs from arbitrary, noisy, or unstructured text using LLMs and provides type-safe output in JSON, YAML, or TOML formats.
Converts text into spoken audio using OpenAI's Text-to-Speech API.
Enables text models to interact with multimodal AI models through a standardized Model Context Protocol (MCP) server.
Provides a secure boilerplate for exposing AI-compatible APIs to various large language models and agents using the Model Context Protocol.
Automates multi-layered security analysis of codebases using AI-driven insights and static analysis rules.
Lints Python and JavaScript code by providing a REST API that returns a lint report in JSON format.
Interacts with a Model Context Protocol server, enabling users to send commands, query data, and manage resources.
Manages todos and integrates with Google Calendar using natural language through OpenAI's Assistant API and Model Context Protocol (MCP).
Enhances conversational agents by combining static document knowledge with dynamic real-time web search capabilities.
Performs mathematical calculations using natural language processing and OpenAI's GPT model.
Enables users to interact with LLMs and MCP-compatible servers from the command line.
Analyzes CSV files by answering questions, plotting graphs, and applying modifications using an AI agent.
Orchestrates multiple agent wrappers and tool servers, presenting a single OpenAI-compatible API to clients.
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