"Interacting with AI models like OpenAI or Google models" matching MCP servers:

A lightweight bridge that wraps OpenAI's built-in tools (like web search and code interpreter) as Model Context Protocol servers, enabling their use with Claude and other MCP-compatible models.

Enables automatic weather information retrieval through a custom MCP server integrated with OpenAI using Cloudflare tunnels. Demonstrates seamless function calling between OpenAI and custom MCP tools without manual intervention.

Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A Model Context Protocol server implementation that enables connection between OpenAI APIs and MCP clients for coding assistance with features like CLI interaction, web API integration, and tool-based architecture.

An auto-generated MCP server that enables interaction with the OpenAI API, allowing users to access OpenAI's models and capabilities through the Multi-Agent Conversation Protocol.

Exposes Gemini CLI's built-in tools and external MCP proxies through a unified MCP endpoint while providing an OpenAI-compatible API for Gemini models. It features configurable security modes to safely manage file system operations, web searches, and shell command execution.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

Enables AI assistants to create and modify Google Apps Script projects, manage versions and deployments, run functions, and inspect execution history through natural language.

Enables AI models to dynamically create and execute their own custom tools through a meta-function architecture, supporting JavaScript, Python, and Shell runtimes with sandboxed security and human approval flows.

Enables automation of Google Jules AI coding assistant through task creation, code review automation, repository management, and AI-powered development workflows. Supports multiple session modes including cloud deployment with persistent authentication.

Enables AI agents to program MicroPython boards such as Raspberry Pi Pico and ESP32 through Thonny, with visible shell commands and optional human approval.

Provides web search and code execution capabilities using OpenAI models, with optional code interpreter and conversation continuity via response IDs.

A code-first MCP server that provides a single tool to execute JavaScript or TypeScript with authenticated access to Google Workspace APIs. It enables flexible interactions with services like Calendar and Drive by running user-provided scripts through a built-in runtime environment.

Provides emergency coding assistance by querying three AI coding models simultaneously through OpenRouter, with automatic premium fallback on rate limits, returning multiple expert opinions with cost and latency telemetry for debugging and problem-solving.

Provides integration with the Google Apps Script API, allowing management of script projects, deployments, versions, and executions through any MCP-compatible client like Claude Desktop or VS Code.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.

A project that integrates Model Control Protocol with OpenAI's API, allowing OpenAI to access and utilize tools exposed by a dockerized MCP server.