"Information about pages or the term 'page'" matching MCP servers:

Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.

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 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.

An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.

Enable Claude Code, Cursor, or your favorite LLM to interact with Xcode, building your projects the same way you do, and seeing the same errors. Greatly increases productivity when working on iOS, iPadOS, macOS, visionOS, tvOS projects & Swift packages - or any time you might use Xcode.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

This server enables natural language interaction between a user and their Kuzu databases using clients like Claude Desktop or Cursor, allowing LLMs to retrieve the database schema, execute Cypher queries, create nodes, and establish relationships in the graph database.

A Model Context Protocol server that retrieves current weather information for any city using the OpenWeatherMap API, designed for integration with Claude Code.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

Bridges Claude Code to a Cloud Orchestrator API, providing access to multi-AI consensus, web search, code execution sandboxes, long-term memory, knowledge graphs, deployment management, and 20+ integrated AI and developer tools.

A simple MCP server that provides a tool to fetch current weather information for cities using the Open-Meteo API, communicating through stdin/stdout.

Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.

A basic Model Context Protocol (MCP) server implementation that provides a foundation for MCP server development. The README doesn't specify particular functionality, suggesting it may be a template or starting point for building custom MCP servers.

A simple demonstration server for the MCP Python SDK that provides weather alerts for locations, allowing users to query weather information through Claude Desktop or Cursor.

A local MCP server that enables AI clients to read ArcGIS Pro project information and execute ArcPy geoprocessing in the native ArcGIS Pro Python environment.

IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real

Fetches up-to-date documentation for any npm package directly in your IDE by retrieving README files from GitHub repositories or package tarballs. Provides real-time access to current package documentation and API information.

A microservice control plane server that integrates with Windsurf IDE by fetching API information from Eolink OpenAPI and exposing it as MCP resources, enabling seamless API integration and management in the development environment.

A remote MCP server that enables AI agents to host HTML pages, generate PDFs, capture screenshots, scrape sites, and run sandboxed code using a CustomJS API key.

Enables AI agents to read, edit, execute cells, and capture outputs from Jupyter notebooks directly within VS Code or Cursor via the Model Context Protocol.