A template project for building Model Context Protocol servers with FastMCP framework, Docker support, and example CRUD API implementation to help developers quickly bootstrap their own MCP servers.
A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.
A low-level computer-use MCP server that exposes raw desktop control (mouse, keyboard, shell, windows, processes, screenshots, etc.) to MCP clients like Claude Code and Codex.
Enables AI assistants to scan project dependencies and Infrastructure as Code files for security vulnerabilities and misconfigurations. It also provides automated fixing capabilities to remediate identified security issues.
A Model Context Protocol server that enables generating and managing Robot Framework test automation with SeleniumLibrary, including test case generation, page object models, and advanced web testing capabilities.
An extensible framework that exposes quantitative research functions and financial data connectors, such as FRED, via an MCP server. It enables users to perform complex financial modelling, data retrieval, and autonomous research loops with built-in guardrails and pluggable components.
Exposes Anthropic's computer-use action surface (screenshot, click, move, keyboard, clipboard, batch) against a persistent desktop display via MCP stdio protocol. Enables AI agents to control a virtual desktop environment through natural language instructions.
Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.
Enables AI applications to use advanced memory management capabilities through the memU AI framework. Supports storing conversation memories, semantic retrieval, multi-user management, and memory statistics via standardized MCP protocol.
Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.
Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.
A lightweight and modular framework for building MCP-based file management systems with standardized module structure, flexible configuration, and extensible functionality registration mechanisms.
Enables AI agents to interact with web browsers using natural language, featuring automated browsing, form filling, vision-based element detection, and structured JSON responses for systematic browser control.