GitHub AI Agent Skills

✨ Features | 🚀 Getting Started | 🎥 Demos | ⚙️ Configuration | 🛠️ Tools | 🧑‍💻 Development A powerful and flexible Kubernetes Model Context Protocol (MCP) server implementation with support for Kubernetes and OpenShift. - ✅ Configuration: - Automatically detect changes in the Kubernetes configuration and update the MCP server. - View and manage the current Kubernetes .kube/config or in-cluster

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A Kubernetes MCP (Model Control Protocol) server that enables interaction with Kubernetes clusters through MCP tools. - Query supported Kubernetes resource types (built-in resources and CRDs) - Kubernetes resource operations with fine-grained control - Read operations: get resource details, list resources by type with filtering options - Write operations: create, update, and delete resources (each

An MCP server focused only on Overleaf projects (via Overleaf Git sync). .env example: - OVERLEAFTOKEN is required. - projectid can be passed per tool call, or use default PROJECTID. - Overleaf Git access requires a plan that supports Git integration. Add to ~/.config/Claude/claudedesktopconfig.json: - Python 3.13+ - uv package manager MIT - See LICENSE

A unified Model Context Protocol server implementation that aggregates multiple MCP servers into one. 1MCP (One MCP) is designed to simplify the way you work with AI assistants. Instead of configuring multiple MCP servers for different clients (Claude Desktop, Cherry Studio, Cursor, Roo Code, Claude, etc.), 1MCP provides a single, unified server. - 🔄 Unified Interface: Aggregates multiple MCP ser

A PTY-based MCP server with strong Windows support, giving MCP-capable AI clients and their agents persistent, interactive shell access via pseudo-terminals (node-pty). Unlike simple exec-based approaches, this keeps PTY-backed shell sessions alive across steps, with bidirectional communication for interactive CLI tools, incremental reads, and session state that carries forward. See the Changelog

Instead of manually writing a system prompt, this tool mines your actual conversation history — your word patterns, recurring topics, and habits of thought — and distils them into a ~3k character profile that meaningfully changes how an AI responds to you. The pipeline runs entirely locally. It never sends your conversation data anywhere. 1. Stream conversations-.json using ijson — never loads the

A Model Context Protocol (MCP) server for the Discord API (JDA), allowing seamless integration of Discord Bot with MCP-compatible applications like Claude Desktop. Enable your AI assistants to seamlessly interact with Discord. Manage channels, send messages, and retrieve server information effortlessly. Enhance your Discord experience with powerful automation capabilities. Manual Installation M

stats-compass-mcp Turn your LLM into a data analyst. Multiple data science tools via MCP. Restart your client and start asking questions about your data. Run stats-compass-mcp list-tools to see all available tools. Start your message with "Use stats compass to..." — this tells the AI to use the Stats Compass tools instead of trying to write code or use other methods. Local mode: Start with "Use st

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test. For the best results, add the following to your custom prompt: This will ensure Cline uses this MCP server to request user feedback before marking the task as completed. Hitting Save Configuration crea

Manage MCP servers across 13 AI clients from one CLI. Define a server once. Enable it where you want. Keep unmanaged client entries intact. MCP servers are useful, but managing them across multiple AI clients is repetitive and error-prone: - different config locations - different formats (JSON, JSONC, TOML) - repeated env/header setup - easy to overwrite manual client entries - hard to roll back a

Slack MCP Server Give Claude the same Slack access you have. DMs, threads, history—no admin approval. I built this because I was working with someone to help me manage a complex workload, and we kept hitting walls. They needed context from my messages—"what did X say about Y?"—but Slack's API blocks access to DMs without admin approval. Screenshotting messages is not a workflow. This server bridge

Own your AI. Agents, memory, tools, and identity that live on your Mac. Built purely in Swift. Fully offline. Open source. Download for Mac · Plugin Registry Models are getting cheaper and more interchangeable by the day. What's irreplaceable is the layer around them -- your context, your memory, your tools, your identity. Others keep that layer on their servers. Osaurus keeps it on your machine.

Version: v0.2.0 An MCP server that provides access to the Postman API. Functionality is based on the official OpenAPI specification. For more information, see the Postman API documentation. This project is part of the Model Context Protocol (MCP) initiative from Anthropic. For more information, visit the MCP GitHub repository and the announcement on the Anthropic blog. Skip ahead to install instru

日本語版 README はこちら An MCP (Model Context Protocol) server that provides structured access to ISO 32000 (PDF) specification documents. Enables LLMs to navigate, search, and analyze PDF specifications through well-defined tools. - Multi-spec support — Auto-discovers and manages up to 17 PDF-related documents (ISO 32000-2, PDF/UA, Tagged PDF guides, etc.) - Structured content extraction — Headings, par

- Fixed reply threading — auto-resolves In-Reply-To and References headers so email replies land in the correct thread instead of creating orphaned messages (upstream PR 91, still pending) - Send-as alias support — optional from parameter for multi-identity email management (send from any configured Gmail alias) - Reply-all tool — replyall automatically fetches the original email, builds To/CC rec

[![][image-banner]][vercel-link] LobeHub is the ultimate space for work and life: to find, build, and collaborate with agent teammates that grow with you. We’re building the world’s largest human–agent co-evolving network. English · 简体中文 · [Official Site][official-site] · [Changelog][changelog] · [Documents][docs] · [Blog][blog] · [Feedback][github-issues-link] [![][github-release-shield]][github-

A feedback loop for people building AI skills and MCP servers. You're building a skill, an MCP server, or a custom prompt strategy that's supposed to make an AI coding assistant better at a specific job. But how do you know it actually works? How do you know your latest commit made things better and not worse? Pitlane gives you the answer. Define the tasks your skill should help with, set up a bas

Verify fix commits address audit findings without new bugs

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF, HTML, DOCX, TXT, Markdown.

light weight MCP for code that just works A super light-weight, effective embedded MCP (AST-based) that understand and searches your codebase that just works! Using CocoIndex - an Rust-based ultra performant data transformation engine. No blackbox. Works for Claude, Codex, Cursor - any coding agent. - Instant token saving by 70%. - 1 min setup - Just claude/codex mcp add works! Please help star

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.

The MCP server calls the Shahnameh API behind the scenes, so you need to keep that running first. Please refer to the repository below for more information: Shahnameh API Also, please bear in mind that the API uses a database, which can be found here: Shahnameh Dataset Create and activate the virtual environment. For example, on macOS: Then run the inspector: این ریپازیتوری تنها یک بخش کوچک از پرو

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 (