LLM & AI Agent Skills

A Model Context Protocol (MCP) server for interacting with Meta Ads. Analyze, manage and optimize Meta advertising campaigns through an AI interface. Use an LLM to retrieve performance data, visualize ad creatives, and provide strategic insights for your ads on Facebook, Instagram, and other Meta platforms. mcp-name: co.pipeboard/meta-ads-mcp - Discord. Join the community. - Email Support. Email u

ScrapeBadger MCP Server Give your AI agents access to Twitter/X data via the Model Context Protocol ScrapeBadger MCP Server is a Model Context Protocol (MCP) server that enables AI assistants like Claude, ChatGPT, Cursor, Windsurf, and other MCP-compatible clients to access Twitter/X data through the ScrapeBadger API. With this MCP server, your AI can: - Get Twitter user profiles, followers, and f

Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces).

An MCP server that enables Claude Desktop, Claude Code, Cursor, or other MCP clients to directly access and process arXiv papers by fetching the LaTeX source. It uses arxiv-to-prompt under the hood to handle downloading and processing the LaTeX. Why use the LaTeX source instead of uploading PDFs? Many PDF chat applications often struggle with mathematical content and equation-heavy papers. By util

Multi-agent AI consultation framework for Claude Code via MCP. Get a second (and third) opinion from other LLMs when Claude Code alone isn't enough. Claude Code is powerful, but one brain can miss bugs, overlook edge cases, or get stuck in a local optimum. Critical decisions benefit from diverse perspectives. Concilium runs parallel consultations with multiple LLMs through standard MCP protocol. E

Connect Claude Code to your Robinhood account. Analyze your portfolio, get real-time quotes, and execute trades—all through conversation. Then in Claude Code: 1. Type /mcp → select trayd → click Authorize 2. Sign in with Google 3. Say: "Link my Robinhood account" 4. Approve on your phone 5. Start trading! Instead of clicking through dozens of screens: Important to understand: - Your Robinhood emai

Enterprise-grade Chrome automation for AI agents with compliance-ready logging Enterprise Features • Compliance Logging • Security Features • Quick Start • Docker Deploy Built for corporate environments where security, compliance, and auditability are non-negotiable. SIEM-ready logging in industry-standard formats. Every tool execution, credential access, and security event is logged. - authentica

LLM evaluation and testing patterns including prompt testing, hallucination detection, benchmark creation, and quality metrics. Use when testing LLM applications, validating prompt quality, implementing systematic evaluation, or measuring LLM performance.

A Model Context Protocol server for Zotero integration. It gives any LLM full access to your Zotero library: search, organize, add papers by DOI, import PDFs, read full-text content, and inject live citations into Word documents. The server is designed to be usable by any LLM without external documentation. On connection, it sends workflow instructions via the MCP instructions field, and each tool

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

Lint any URL for LLM readiness. Get a 0-100 score for token efficiency, RAG readiness, agent compatibility, and LLM extraction quality. Context CLI is an LLM Readiness Linter that checks how well a URL is structured for AI consumption. As LLM-powered search engines, RAG pipelines, and AI agents become primary consumers of web content, your pages need to be optimized for token efficiency, structure

Zero-hallucination answers • Gemini Deep Research • 14 Security Layers • Enterprise Compliance What's New 2026 • Deep Research • Document API • Create Notebooks • Security • Install - 🔍 Query your NotebookLM notebooks — source-grounded, zero-hallucination answers - 📚 Create & manage notebooks programmatically — no manual clicking - 🎙️ Generate audio overviews — podcast-style summaries of your d

The open-source alternative to Google's Code Wiki — with MCP. Index any codebase with tree-sitter, generate docs with your LLM, serve them through a full-featured docs site, and expose everything as tools for coding agents via MCP. Like Notion for code agents. Index a project and generate documentation. Defaults to the current directory. Start the docs server. Manage API keys and provider settings

The goal of this MCP is to: - Consolidate ESP-IDF and related project commands in one place. - Simplify getting started using only LLM communication. Simply find a command that is missing from this MCP and create a PR for it! If you want someone to help you with this implementation, just open an issue. This project is currently a Proof of Concept (PoC) for an MCP server tailored for ESP-IDF workfl

Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.

Smart context management for LLM development workflows. Share relevant project files instantly through intelligent selection and rule-based filtering. Getting the right context into LLM conversations is friction-heavy: - Manually finding and copying relevant files wastes time - Too much context hits token limits, too little misses important details - AI requests for additional files require manual

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

The Unitree Go2 MCP Server is a server built on the Model Context Protocol (MCP) that enables users to control the Unitree Go2 robot using natural language commands interpreted by a Large Language Model (LLM). These commands are translated into ROS2 instructions, allowing the robot to perform corresponding actions. - Unitree Go2 robot - Ubuntu 20.04 or 22.04 - ROS2 environment : Humble(recommended

A Mattermost integration that connects to Model Context Protocol (MCP) servers, leveraging a LangGraph-based AI agent to provide an intelligent interface for interacting with users and executing tools directly within Mattermost. - 🤖 Langgraph Agent Integration: Uses a LangGraph agent to understand user requests and orchestrate responses. - 🔌 MCP Server Integration: Connects to multiple MCP serve

MKP is a Model Context Protocol (MCP) server for Kubernetes that allows LLM-powered applications to interact with Kubernetes clusters. It provides tools for listing and applying Kubernetes resources through the MCP protocol. - List resources supported by the Kubernetes API server - List clustered resources - List namespaced resources - Get resources and their subresources (including status, scale,

This project is a MCP server for automating and managing interactions on a Facebook Page using the Facebook Graph API. It exposes tools to create posts, moderate comments, fetch post insights, and filter negative feedback — ready to plug into Claude, or other LLM-based agents. This MCP provides a suite of AI-callable tools that connect directly to a Facebook Page, abstracting common API operations

A personal filesystem that works as your life operating system — designed to be read, queried, and operated on by an AI agent. Life OS is a structured set of markdown files that give an AI agent (Goose, Claude, or any LLM with filesystem access via MCP) persistent context about your life — who you are, what you're working on, what you're learning, and what's happened. The AI reads these files at t