GitHub AI Agent Skills

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. This document outlines the setup process and provides a basic example of using the client. Ingest anything from Slack, Discord, websites, Google Drive, email, Jira, Linear or GitHub into a Graphlit project - and then search and retrieve relevant knowledge within an MCP client like Cursor, Wind

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A Model Context Protocol server for generating charts using AntV. We can use this mcp server for chart generation and data analysis. This is a TypeScript-based MCP server that provides chart generation capabilities. It allows you to create various types of charts through MCP tools. You can also use it in Dify. - ✨ Features - 🎨 Skill Usage - 🚰 Run with SSE or Streamable transport - 🎮 CLI Options

MCP server for spatial transcriptomics analysis via natural language Using Claude Code / Codex / OpenCode? Just paste this: Manual installation See Installation Guide for detailed setup including virtual environments and all MCP clients. 60+ methods across 15 categories. Supports 10x Visium, Xenium, Slide-seq v2, MERFISH, seqFISH. MIT License · GitHub · Issues

A Model Context Protocol (MCP) server that transforms how you interact with Google Search Console, Bing Webmaster Tools, and Google Analytics 4. Stop exporting CSVs and start asking questions. 📚 View Documentation Data Silos: Manually checking Google, then Bing, then GA4. Manual Correlation: Exporting 3 different CSVs and using VLOOKUPs to see if your 1 ranking page actually converts. Switching F

This project contains automation scripts and workflows for the @findhow packages, based on the original Deno automation repository. The goal is to provide consistent and efficient automation for the @findhow ecosystem.

Automate GitHub repositories, issues, pull requests, branches, CI/CD, and permissions via Rube MCP (Composio). Manage code workflows, review PRs, search code, and handle deployments programmatically.

A Model Context Protocol (MCP) server that allows controlling macOS through SwiftAutoGUI. This server provides tools for programmatically controlling the mouse and keyboard through MCP clients. - macOS 15.0 or later - Swift 6.0 or later - Xcode 16.0 or later 1. Clone this repository: 3. Add command to your MCP client. The server provides the following tools for controlling macOS: - Tool name: move

Production-Ready Model Context Protocol (MCP) server that enables AI assistants to fully interact with console applications, monitor output, detect errors, and automate terminal workflows - similar to how Playwright works for web browsers. This server is fully production-ready with: - ✅ No native compilation required (removed node-pty dependency) - ✅ Full cross-platform support (Windows, macOS, Li

Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.

Make your meetings accessible to AI Agents 🤖 joinly.ai is a connector middleware designed to enable AI agents to join and actively participate in video calls. Through its MCP server, joinly.ai provides essential meeting tools and resources that can equip any AI agent with the skills to perform tasks and interact with you in real time during your meetings. - Live Interaction: Lets your agents exec

A modular and extensible Model Context Protocol (MCP) server for Jira and GitHub integration, enabling end-to-end automation of developer workflows - from issue tracking to code changes and pull request management - via AI agents inside the IDE. - Jira integration: fetch issues by filters, search via JQL, and transition issues across workflows - GitHub integration: create branches, open and merge

Advanced filesystem operations for Claude Desktop with large file handling capabilities and Claude-optimized features. Add to your Claude Desktop config. - Basic setup - With backup files enabled Control backup file creation behavior. - CREATEBACKUPFILES=false (default): Disables backup file creation to reduce clutter - CREATEBACKUPFILES=true: Creates backup files before modifications Note: Backup

An MCP server that connects to OPC UA-enabled industrial systems, allowing AI agents to monitor, analyze, and control operational data in real time. This project is ideal for developers and engineers looking to bridge AI-driven workflows with industrial automation systems. - Read OPC UA Nodes: Retrieve real-time values from industrial devices. - Write to OPC UA Nodes: Control devices by writing va

mcp-name: io.github.wmarceau/fitness-influencer AI-powered automation suite for fitness content creators. Automates video editing, graphics creation, email management, SMS communication, and revenue analytics. Production URL: https://fitness-influencer-production.up.railway.app (if deployed) When running the API server: Located at: .claude/skills/fitness-influencer-operations/SKILL.md Trigger phra

An MCP (Model Context Protocol) server that connects Claude with Todoist for complete task and project management through natural language. 1. Download todoist-mcp.mcpb from the latest release 2. Double-click the file (or drag onto Claude Desktop) 3. Enter your Todoist API token when prompted 4. Start chatting: "Show me my Todoist projects" Manual JSON configuration Add to your MCP client config (

A powerful Model Context Protocol (MCP) server that gives AI real-time vision capabilities and enhanced UI intelligence. Transform your AI assistant into a visual powerhouse that can see, analyze, and interact with your screen content. ScreenMonitorMCP v2 is a revolutionary MCP server that bridges the gap between AI and visual computing. It enables AI assistants to capture screenshots, analyze scr

A Model Context Protocol (MCP) server for Google Sheets API integration. Enables reading, writing, and managing Google Sheets documents directly from your MCP client (e.g., Claude Code, Claude Desktop, Cursor, etc.). - Complete Google Sheets Integration: Read, write, and manage spreadsheets - Advanced Operations: Batch operations, formatting, charts, and conditional formatting - Flexible Authentic

-brightgreen) A Model Context Protocol (MCP) server for analyzing technical debt across multiple programming languages. Designed to integrate with GitHub Copilot and other MCP-compatible tools. - Multi-language support: JavaScript, TypeScript, Python, Java, Swift, Kotlin, Objective-C, C++, C, C, Go, Rust, Ruby, PHP - Comprehensive analysis: Detects various types of tech debt including code quality

Local-first MCP runtime for multi-agent consensus guard workflows — AI code review, weighted voting, HITL approval gates, and full observability on SQLite. MCP stdio mode (Claude Desktop, OpenClaw, etc.): Prerequisites: Node.js 20+, npm 10+. Optional: gh CLI (for GitHub PR triggers), OpenAI API key (falls back to deterministic heuristics without one). Any model accessible via the OpenAI or Anthrop

The Wanaku MCP Router is a router for AI-enabled applications powered by the Model Context Protocol (MCP). This protocol is an open protocol that standardizes how applications provide context to LLMs. The project name comes from the origins of the word Guanaco, a camelid native to South America. - Unified Access - Centralized routing and resource management for AI agents - MCP-to-MCP Bridge - Act

A TypeScript framework for building MCP servers capable of handling client sessions. - Simple Tool, Resource, Prompt definition - Authentication - Passing headers through context - Session ID and Request ID tracking - Image content - Audio content - Error handling - HTTP Streaming (with SSE compatibility) - HTTPS Support for secure connections - Custom HTTP routes for REST APIs, webhooks, and admi

Generate Apache ECharts with AI MCP dynamically for chart generation and data analysis. Also you can use mcp-server-chart to generate chart, graph, map. - Fully support all features and syntax of ECharts, include data, style, theme and so on. - Support exporting to png, svg, and option formats, with validation for ECharts to facilitate the model's multi-round output of correct syntax and graphics.

This downloads the latest release and installs it to /Applications. 1. Download the latest MemoryLane Setup .exe from GitHub Releases. 2. Run the installer and finish setup. 3. Launch MemoryLane from the Start menu. Desktop app that sees what you see, stores summaries about it locally and lets you query it in any AI chat via MCP. Screenshots → local storage → MCP into AI chats Once connected, try