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Automatically converts JavaScript modules into MCP-compatible servers, making any JavaScript function accessible to AI systems through secure sandboxing with automatic type inference.

An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.

A specialized MCP server for SAPUI5 and Fiori development that enables code generation, project analysis, and refactoring for JavaScript-based applications. It provides comprehensive tools for managing OData features, validating code compatibility, and searching official SAPUI5 SDK and MDN documentation.

"mcp\_scholar" is a Python-based tool for searching and analyzing Google Scholar papers, supporting features like keyword-based searches and integration with MCP clients and Cherry Studio. It provides functionalities such as fetching top-cited papers from scholar profiles and summarizing research top

MCP Scratchpad

A scratchpad repository for MCP clients/servers.

A small Model Context Protocol (MCP) server that gives an LLM eyes on your desktop without burning context. It can take one-off screenshots, crop a region around the mouse cursor, and run timed streaming sessions that save frames to disk and only return image bytes when explicitly asked.

Enables LLMs to capture and analyze screenshots of your screen, windows, or regions with smart detection capabilities. Features natural language queries, automatic window targeting, and text enhancement for UI debugging and visual inspection.

Enables capturing screenshots and annotating images with boxes, arrows, text, highlights, and other shapes, plus editing features like blur, crop, and resize with flexible export options.

Provides screen capture and optical character recognition (OCR) capabilities for entire displays or specific application windows. It enables users to list running applications, take screenshots, and extract text from images using multi-language support.

A standalone MCP server that exposes API endpoints as tools for AI assistants by proxying requests to a target API defined in an OpenAPI specification. It supports various authentication methods and utilizes Server-Sent Events (SSE) to facilitate integration with clients like Claude and ChatGPT.

A standalone MCP server that exposes Eyra Accelerator API endpoints as tools for AI assistants via SSE transport. It enables secure interaction with the target API by proxying requests and handling authentication automatically.

A standalone MCP server that exposes Petstore API endpoints as tools for AI assistants like Claude and ChatGPT. It enables interaction with petstore management services through natural language by proxying API requests via SSE transport.

An MCP server generated from an OpenAPI specification that exposes Petstore API endpoints as tools for AI assistants. It enables interaction with pet store management functionalities using the Model Context Protocol over SSE transport.

A standalone MCP server generated from an OpenAPI specification that exposes Petstore API endpoints as tools for AI assistants. It utilizes SSE transport to enable models to interact with pet store management functionalities through natural language.

Exposes Petstore API endpoints as tools for AI assistants using the Model Context Protocol via SSE transport. It enables users to interact with the Petstore service through natural language by proxying requests to the target API.

Automatically installs and containerizes MCP servers from GitHub repositories using MCP sampling to analyze repositories and create appropriate Docker images.

A Python-based FastMCP server that provides financial tools for securities analysis, including market data, news, fundamental/technical analysis, and visualization capabilities that can be consumed by any MCP-aware client.

MCP Selenium Grid

(DO NOT USE, NOT READY) A Model Context Protocol (MCP) server that enables AI Agents to request and manage Selenium browser instances through a secure API. Perfect for your automated browser testing needs! 🚀

A Model Context Protocol server implementation that enables browser automation through standardized MCP clients, supporting features like navigation, element interaction, and screenshots across Chrome, Firefox, and Edge browsers.

Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.