LLM & AI Agent Skills

A tool similar to cloc, sloccount and tokei. For counting the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages. Goal is to be the fastest code counter possible, but also perform COCOMO calculation like sloccount, LOCOMO estimation for LLM-based development costs, estimate code complexity similar to cyclomatic complexity calculators and prod

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.

An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data. - osm-mcp-server: The main server, available for public use. This server provides LLMs with tools to interact with OpenStreetMap data, enabling location-based applications to: - Geocode addresses and place names to coordinates - Reverse geocode coordinates to addresses - Find

aka Vibe Debugging This is an MCP Server and VS Code extension which enables claude to interactively debug and evaluate expressions. That means it should also work with other models / clients etc. but I only demonstrate it with Claude Desktop and Continue here. It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode. 1. Download the extension from re

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.

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

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 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

Connect Open Data to LLMs in minutes! We enable 2 things: Open Data Access: Access to many public datasets right from your LLM application (starting with Claude, more to come). Publishing: Get community help and a distribution network to distribute your Open Data. Get everyone to use it! How do we do that? Access: Setup our MCP servers in your LLM application in 2 clicks via our CLI tool (starting

You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur

See a demo here: https://www.youtube.com/watch?v=KG6TMLD8GmA Upload, edit, search, and generate videos from everyone's favorite LLM and Video Jungle. You'll need to sign up for an account at Video Jungle in order to use this tool, and add your API key. The server implements an interface to upload, generate, and edit videos with: - Custom vj:// URI scheme for accessing individual videos and project

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

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

Guide for upgrading Stripe API versions and SDKs

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

An MCP (Model Context Protocol) server that brings authoritative medical information into AI coding environments like Cursor and Claude Desktop. - 🔒 Your Data Never Leaves – Runs 100% locally; no tracking, no logs, no cloud - 🆓 No API Keys – Works out of the box, zero configuration - 🏥 Authoritative Sources – FDA, WHO, PubMed, RxNorm, Google Scholar, AAP, pediatric journals - ⚡ Easy Setup – One

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).

Model Context Protocol (MCP) Server for Langfuse Prompt Management. This server allows you to access and manage your Langfuse prompts through the Model Context Protocol. Quick demo of Langfuse Prompts MCP in Claude Desktop (unmute for voice-over explanations): This server implements the MCP Prompts specification for prompt discovery and retrieval. - prompts/list: List all available prompts - Optio

The Parallel Search MCP allows using Parallel Search API from within any MCP-compatible LLM client. It is meant for daily use for everyday smaller web-search tasks. Please read our MCP docs here for more details. The official installation instructions can be found here. Running locally This is a Search MCP proxy server (https://search-mcp.parallel.ai) that proxies /mcp to https://mcp.parallel.ai/v

MCP server for the Urlbox Screenshot API. Enables your client to take screenshots, generate PDFs, extract HTML/markdown, and more from websites. Visit Urlbox for more information, and have a read of our docs or chat with your LLM post install to get a good understanding of its options and capabilities. 1. Install dependencies and build: 2. Get Urlbox API credentials: - Sign up at urlbox.com - Get

Please migrate to our new KnowledgeBase MCP Server, which provides enhanced capabilities and improved accuracy. Model Context Protocol (MCP) is a standardized protocol designed to manage context between large language models (LLMs) and external systems. The Chargebee MCP Server offers a robust set of tools to improve developer efficiency. It integrates with AI-powered code editors like Cursor, Win