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Provides a collection of MCP tools.
Enables AI assistants to interact with and manage Harvester HCI clusters via natural language.
Demonstrates how to construct an MCP server with minimal code.
Enables interaction with Neo4j databases directly from the Cursor IDE.
Facilitates interaction with the Hedera network by providing tools for wallet creation, balance checks, and transaction management.
Provides a proof-of-concept server for streaming Model Context Protocol (MCP) data via Server-Sent Events (SSE) using STDIO transport.
Exposes FileMaker scripts as dynamically created tools using a local Model Context Protocol (MCP) server.
Integrates OpenWeatherMap API to provide comprehensive weather data and forecasts for AI assistants.
Integrates the Yogosha Bug Bounty Platform API into the Model Context Protocol (MCP) ecosystem, enabling programmatic interaction and automation.
Facilitates AI assistant interaction with the HackTheBox platform, providing programmatic access for CTF management and user activities.
Enables AI to directly design and build software prototypes using HTML, bypassing traditional design tools like Figma or Axure.
Monitor and report token usage and costs for OpenAI and Claude APIs, including support for the Model Context Protocol.
Applies AI-powered UX/UI best practices to React components built with Material-UI.
Empowers AI coding agents to control and inspect a live Chrome browser, granting full access to Chrome DevTools for comprehensive web automation, debugging, and performance analysis.
Enables AI assistants to interact with Anki decks for enhanced studying, card creation, and progress analysis.
Provides a universal camera interface and vision tools for AI assistants, enabling them to capture and process images.
Empowers AI agents to systematically create, query, and maintain architecture decision records within a structured SQL database.
Exposes Swagger and OpenAPI document query tools to AI assistants and MCP clients for API interaction.
Enables AI assistants to manage translation assets and localizations through the Loco API.
Exposes Agent Skills as MCP tools, making them available to any compatible agent through a declarative, package.json-based configuration.
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