A specialized MCP server providing LLM enhancement prompts and jailbreaks with dynamic schema adaptation, designed to augment AI capabilities via the MCP protocol.

Enables interactive LLM workflows by adding local user prompts and chat functionality directly into the MCP loop, enhancing the interactivity of MCP servers.

An MCP server for integrating Raindrop.io bookmarks with LLMs using the Model Context Protocol.

A Python-based MCP server that exposes OpenAI's built-in web_search tool as an MCP-compliant service.

A Python-based framework that connects LLMs to executable Python code via MCP User Defined Functions, allowing data scientists to extend models. Directly relevant as a framework for building extensible MCP servers.

An open-source Model Context Protocol (MCP) server with a Python/Node.js hybrid architecture. Features include automatic API documentation parsing, self-healing connection pools, and GDPR-compliant audit trails, making it a robust solution for secure and scalable AI integration.