GitHub AI Agent Skills

English | 简体中文 🧠 The data layer for AI systems. Skill Seekers turns any documentation, GitHub repo, or PDF into structured knowledge assets—ready to power AI Skills (Claude, Gemini, OpenAI), RAG pipelines (LangChain, LlamaIndex, Pinecone), and AI coding assistants (Cursor, Windsurf, Cline) in minutes, not hours. Skill Seekers is the universal preprocessing layer that sits between raw documentatio

An unofficial CellarTracker Remote MCP Server hosted on Cloudflare Workers. This will deploy your MCP server to a URL like: cellartracker. .workers.dev/mcp

Generate images and videos using fal.ai AI models

A Wolfram Alpha-like skill for solving mathematical problems, converting units, and retrieving factual data.

Born from a Reddit thread and months of iteration, The Agency is a growing collection of meticulously crafted AI agent personalities. Each agent is: - Specialized: Deep expertise in their domain (not generic prompt templates) - Personality-Driven: Unique voice, communication style, and approach - Deliverable-Focused: Real code, processes, and measurable outcomes - ✅ Production-Ready: Batt

GitHub patterns using gh CLI for pull requests, stacked PRs, code review, branching strategies, and repository automation. Use when working with GitHub PRs, merging strategies, or repository management tasks.

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

The firewall for AI agents. Open-source policy enforcement for MCP. Website: policylayer.com Intercept is a deterministic enforcement proxy for the Model Context Protocol (MCP). It sits between an AI agent and an MCP server, evaluating every tools/call request against YAML-defined policies. Violating calls are blocked at the transport layer before reaching the upstream server. MCP gives AI agents

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 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

A Model Context Protocol (MCP) server for LinkedIn. Search people, companies, and jobs, scrape profiles, and retrieve structured JSON data from any MCP-compatible AI client. Built with FastMCP, Patchright, and a clean hexagonal architecture. The getpersonprofile tool supports granular section scraping. Request only the sections you need: - Main profile (always included) — name, headline, location,

Let AI agents see, understand, and interact with your React Native app running on Android emulator or iOS simulator — through a single MCP server. Point your MCP client at this server and an agent can connect to your app, read logs, inspect the UI, tap buttons, type text, scroll, take screenshots, and reload — all without leaving the conversation. - Android + iOS — one server handles both platform

An Android application that runs as an MCP (Model Context Protocol) server, enabling AI models to fully control an Android device remotely using accessibility services and screenshot capture. The app runs directly on your Android device (or emulator) and exposes an HTTP server (with optional HTTPS) implementing the MCP protocol. AI models like Claude can connect to it and interact with any app on

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

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

AI can build products. But it still doesn't talk to users. Usercall MCP lets AI agents run user interviews via voice calls and return structured insights with themes and verbatim quotes. Works with Claude Desktop, Cursor, and any MCP-compatible client. AI agents can now build and ship products extremely quickly. But most agents still rely on synthetic feedback or assumptions about users. Usercall

knowledge-to-action-mcp is an MCP server for people whose real project context lives in notes, decisions, roadmaps, and meeting docs, not just code. Most Obsidian MCP servers stop at "read a note" or "search a vault." This one goes further: That means an MCP client can move from: If you work out of Obsidian, your important context is usually spread across: - roadmap notes - meeting notes - decisio

- About the pgEdge Postgres MCP Server - pgEdge Postgres MCP Server - Choosing the Right Solution - Best Practices - Querying the Server - Installing the MCP Server - Quick Start - Quickstart Demo with Northwind - Deploying on Docker - Deploying from Source - Testing the MCP Server Deployment - Configuring the MCP Server - Specifying Configuration Preferences - Using Environment Variables to Speci

Instead of manually checking the Rybbit dashboard, let your AI assistant query analytics data directly: - "How many users visited the site today?" - "Show me the top pages by bounce rate this week" - "What errors occurred in the last hour?" - "Show user journey from homepage to checkout" - "Compare browser usage between mobile and desktop" Or clone and build: Add to your ~/.claude/settings.json or

The ultimate Rust SDK and high-performance MCP server for Obsidian-flavored Markdown (.ofm) and standard .md vaults. TurboVault is a dual-purpose toolkit designed for both developers and users. It provides a robust, modular Rust SDK for building applications that consume markdown directories, and a full-featured MCP server that works out of the box with Claude and other AI agents. Build your own a

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

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

Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.

An MCP server that exposes Wireshark/tshark capabilities to AI tools and IDEs. Capture live traffic, analyze .pcap files, apply display filters, follow TCP/UDP streams, and export to JSON — all via Claude Desktop, VS Code Copilot, or any MCP-compatible client. - Python 3.10+ - Wireshark/tshark installed and on PATH Linux: add your user to the wireshark group for non-root capture: Or with uv: ~/Lib