Mcp Server AI Agent Skills

A Model Context Protocol (MCP) server implementation for Azure Data Lake Storage Gen2. This service provides a standardized interface for interacting with ADLS2 storage, enabling file operations through MCP tools. Requires Python 3.13 or higher. Install the package using uv: 1 - Edit Claude Desktop Configuration: Open claudedesktopconfig.json and add the following configuration. On MacOs, the file

The is a remote MCP server that wraps the TripGo API and provides the following tools: - tripgo-locations: Retrieve transport-related locations - tripgo-departures: Departures from a specific public transport stop - tripgo-routing: Mixed and multi-modal trip planning - tripgo-get-trip-url: Get the URL of a trip previously calculated using the tripgo-routing tool The MCP server is deployed on Cloud

日本語版 README はこちら Translation quality evaluation MCP Server powered by xCOMET (eXplainable COMET). xCOMET MCP Server provides AI agents with the ability to evaluate machine translation quality. It integrates with the xCOMET model from Unbabel to provide: - Quality Scoring: Scores between 0-1 indicating translation quality - Error Detection: Identifies error spans with severity levels (minor/major/c

The GitHub MCP Server connects AI tools directly to GitHub's platform. This gives AI agents, assistants, and chatbots the ability to read repositories and code files, manage issues and PRs, analyze code, and automate workflows. All through natural language interactions. - Repository Management: Browse and query code, search files, analyze commits, and understand project structure across any reposi

CSL-Core (Chimera Specification Language) is a deterministic safety layer for AI agents. Write rules in .csl files, verify them mathematically with Z3, enforce them at runtime — outside the model. The LLM never sees the rules. It simply cannot violate them. Originally built for Project Chimera, now open-source for any AI system. This doesn't work. LLMs can be prompt-injected, rules are probabilist

A Model Context Protocol (MCP) server implementation for running Locust load tests. This server enables seamless integration of Locust load testing capabilities with AI-powered development environments. - Simple integration with Model Context Protocol framework - Support for headless and UI modes - Configurable test parameters (users, spawn rate, runtime) - Easy-to-use API for running Locust load

A weather forecast MCP (Model Context Protocol) server providing 8-day global weather forecasts and current weather conditions using the OpenWeatherMap One Call API 3.0. Animation showing Claude Desktop processing the weather data from the MCP Server Claude Desktop showing a detailed weather forecast with lawn mowing recommendations - 🌍 Support for querying weather conditions anywhere in the worl

An MCP (Model Context Protocol) server that provides token-efficient access to OpenAPI (v3.0) and Swagger (v2.0) specifications via MCP Resource Templates. The primary goal of this project is to allow MCP clients (like Cline or Claude Desktop) to explore the structure and details of large OpenAPI specifications without needing to load the entire file into an LLM's context window. It achieves this