GitHub AI Agent Skills

The wizzy-mcp-tmdb project is an MCP (Model Context Protocol) server implemented in JavaScript that provides tools to search and retrieve information from The Movie Database (TMDB). It allows AI clients to access movie, TV show, and person data through a standardized protocol. - Search Movies: Perform multi-search across movies, TV shows, and people using the searchtmdb tool. - Get Details: Fetch

⭐ Like this project? Please star the repository on GitHub to show your support and stay updated! ⭐ Modern AI-powered coding assistants (like Cursor, Cline, Roo Code, etc.) excel at understanding code structure and syntax but often struggle with the specifics of rapidly evolving libraries and frameworks, especially in ecosystems like Rust where crates are updated frequently. Their training data cut

ACP to MCP Adapter Connect ACP Agents to MCP Applications Seamlessly The ACP to MCP Adapter is a lightweight standalone server that acts as a bridge between two AI ecosystems: Agent Communication Protocol (ACP) for agent-to-agent communication and Model Context Protocol (MCP) for connecting AI models to external tools. It allows MCP applications (like Claude Desktop) to discover and interact with

MCP Toolbox for Databases is an open source MCP server for databases. It enables you to develop tools easier, faster, and more securely by handling the complexities such as connection pooling, authentication, and more. This README provides a brief overview. For comprehensive details, see the full documentation. - Why Toolbox? - General Architecture - Getting Started - Installing the server - Runni

Academic-focused graph analysis in your AI conversations - The first and only NetworkX MCP server specialized for academic research and citation analysis. NetworkX MCP Server enables Large Language Models (like Claude) to perform sophisticated academic research and citation analysis directly within conversations. Built specifically for researchers, academics, and students who need to analyze citat

Firebase MCP enables AI assistants to work directly with Firebase services, including: - Firestore: Document database operations - Storage: File management with robust upload capabilities - Authentication: User management and verification The server works with MCP client applicatios such as Claude Desktop, Augment Code, VS Code, and Cursor. - Firebase project with service account credentials - Nod

An AI coding assistant built in Rust that provides both command-line and graphical interfaces for autonomous code analysis and modification. Multi-Modal Tool Execution: Adapts to different LLM capabilities with pluggable tool invocation modes - native function calling, XML-style tags, and triple-caret blocks - ensuring compatibility across various AI providers. Real-Time Streaming Interface: Advan

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Download the MCPBundles Hub .mcpb file directly: Download hub.mcpb This .mcpb package contains a pre-configured MCP server proxy that connects to the MCPBundles Hub endpoint. Once installed, your AI assistant can discover and execute tools from all your enabled bundles. MCP Bundles is the simplest way to connect AI assistants to real-world tools. Instead of configuring hundreds of individual MCP s

English Version 一个用于与语雀 API 集成的 Model-Context-Protocol (MCP) 服务器。此实现受 Figma-Context-MCP 的启发，并使用 语雀开放 API。 该服务器提供了与语雀知识库平台交互的 MCP 工具，允许 AI 模型： - 获取用户和文档信息 - 创建、读取、更新和删除文档 - 获取统计数据和分析信息 要使用 Smithery 将 Yuque MCP Server 自动安装到 Claude 桌面端： - Node.js 18+ (推荐) - 拥有 API 令牌的语雀账号 3. 基于 .env.example 创建 .env 文件： 4. (可选) 在 .env 文件中添加你的语雀 API 令牌： 你也可以选择在连接到服务器时通过查询参数提供令牌，而不是在 .env 文件中设置。 然后在 HTTP 或 CLI 模式下运行： 本项

- Requirements - Entity Operations - Telemetry Management - Relations - OTA Packages - Entity Data Query - Quick Start Guide - Installation - Docker Image - Build from Sources - Client Configuration - Binary Configuration - Docker Configuration - Environment Variables - Tool Groups Configuration - Available Tools - Device Tools - Asset Tools - Customer Tools - User Tools - Alarm Tools - OTA Tools

Dependency intelligence infrastructure for AI assistants and agents working with JVM projects. Traditional upgrade workflow: 1. Google "Spring Boot 2.7 to 3.2 migration guide" (5 minutes) 2. Read 50-page migration docs, cross-reference breaking changes (15 minutes) 3. Check Maven Central for compatible dependency versions (5 minutes) 4. Update pom.xml, compile, fix breaking changes (30 minutes) 5.

This is an MCP server that analyzes the screen with OmniParser and automatically operates the GUI. Confirmed on Windows. This is MIT license, but Excluding submodules and sub packages. OmniParser's repository is CC-BY-4.0. Each OmniParser model has a different license (reference). 1. Please do the following: (Other than Windows, use export instead of set.) (If you want langchainexample.py to work,

[![MIT licensed][mit-badge]][mit-url] [![Python Version][python-badge]][python-url] [![PyPI version][pypi-badge]][pypi-url] [mit-badge]: https://img.shields.io/pypi/l/mcp.svg [mit-url]: https://github.com/reeeeemo/ancestry-mcp/blob/main/LICENSE [python-badge]: https://img.shields.io/pypi/pyversions/mcp.svg [python-url]: https://www.python.org/downloads/ [pypi-badge]: https://badge.fury.io/py/mcp-s

This project provides a Model Context Protocol (MCP) server wrapper around the esp-rainmaker-cli Python library. It allows MCP-compatible clients (like LLMs or applications such as Cursor, Claude Desktop, and Windsurf) to interact with your ESP RainMaker devices using the official CLI. The Model Context Protocol (MCP) is a standardized framework that enables AI systems to interact with external to

AI-powered debugging and inspection for Kubernetes clusters using Inspektor Gadget. - AI-powered interface for Kubernetes troubleshooting and monitoring - One-click Inspektor Gadget deployment and removal - Intelligent output summarization and analysis - Automatic gadget discovery from Artifact Hub 1. Ensure you have Docker and a valid kubeconfig file 2. Configure the MCP server in VS Code (see IN

Chat with your Kubernetes cluster using natural language! This project connects OpenWebUI to Kubernetes, letting you manage your cluster through conversational AI. Ask questions like "What pods are running?" or "Scale my deployment to 5 replicas" and get instant results. - Quick Start - Configure Open-WebUI - Step 1: Access Open-WebUI - Step 2: Add the MCP Bridge Tool Server - Step 3: Add Connecti

Expert capability for robust, stealthy, and efficient browser automation using Playwright Go.

An MCP server that provides real-time cross-chain bridge metrics, enabling AI agents to analyze liquidity, transaction flows, and performance across blockchain networks. - List Chains: Retrieve a list of all chain slugs from DeFiLlama, sorted by Total Value Locked (TVL) in descending order. - List Bridges: Fetch all bridges, optionally including chain breakdowns, sorted by 24-hour volume. - Histor

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

Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.

See through your agent's eyes. Visualize legacy code, inspect complex flows, understand everything. - Visualize Anything: Use your coding agent to generate on-demand architecture, code, and process diagrams to view your code from different perspectives. - Vibe Checks: AI-generated code can accumulate unused and redundant constructs. Use visualizations to spot areas that need cleanup. - Local Proce

CLI and MCP server for LinkedHelper automation. This project is brought to you by Alexey Pelykh. lhremote lets AI assistants (Claude, etc.) control LinkedHelper through the Model Context Protocol. It can: - App management — detect, launch, and quit LinkedHelper instances - Account & instance control — list accounts, start/stop instances, check status - Campaign automation — create, configure, star

mcp-name: io.github.wmarceau/rideshare-comparison Compare Uber and Lyft prices for any route using Claude Desktop. Add to your claudedesktopconfig.json: Compare Uber and Lyft prices for a specific route. Example prompt: "Compare Uber and Lyft prices from SFO airport to downtown San Francisco" Get a list of cities with rideshare pricing data. Example prompt: "Which cities are supported for rideshar