Gemini AI Agent Skills

MCP (Model Context Protocol) server for the Oyemi semantic lexicon. Provides deterministic word-to-code mapping and valence analysis for AI agents like Claude, ChatGPT, and Gemini. - Semantic Encoding: Convert words to deterministic semantic codes - Valence Analysis: Analyze text sentiment using lexicon-based valence - Semantic Similarity: Measure how similar two words are - Synonym/Antonym Lookup

501 algorithmic trading skills · 16 engineering domains · 5 regulatory & exchange frameworks · 501 working reference implementations backed by 20,291 unit tests · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI and any tool that reads SKILL.md · Apache 2.0 Get Started · What's Inside · How It's Verified · Frameworks & Standards · Platforms · Contribu

A multi-model AI orchestration MCP server for automated code review and LLM-powered analysis. Multi-MCP integrates with Claude Code CLI to orchestrate multiple AI models (OpenAI GPT, Anthropic Claude, Google Gemini) for code quality checks, security analysis (OWASP Top 10), and multi-agent consensus. Built on the Model Context Protocol (MCP), this tool enables Python developers and DevOps teams to

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

Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

A modern, cross-platform Model Context Protocol (MCP) server that enables AI assistants to browse and interact with both Gopher protocol and Gemini protocol resources safely and efficiently. The Gopher & Gemini MCP Server bridges vintage and modern alternative internet protocols with AI assistants, allowing LLMs like Claude to explore the unique content and communities that thrive on both Gophersp

A Model Control Protocol (MCP) server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, VSCode with Copilot, etc. - MCP Compatible: Works out-of-the-box with any MCP client tha

A professional Model Context Protocol (MCP) server that provides a comprehensive toolkit for interacting with Instagram. This server enables LLMs (like Claude or Gemini) to manage accounts, analyze social graphs, discover content, and engage with the Instagram community directly from their interface. - Full Account Control: Edit profile, manage privacy, and track activity. - Advanced Messaging: Re

English Version 基于 Google 的 Imagen 3.0 的图像生成工具，通过 MCP（Model Control Protocol）提供服务。 画一只奔跑的杰克罗素犬，长焦镜头，阳光透过狗狗的毛发，照片级画质 画一个科技感十足的苹果 - 有效的 Google Gemini API 密钥 1. 从 GitHub Releases 下载最新版本的可执行文件 2. 将下载的可执行文件放置在系统中的任意位置，例如 C:\bin\imagen3-mcp.exe 3. 在 Cherry Studio 中配置： - Command 字段填写可执行文件路径，例如 C:\bin\imagen3-mcp.exe - 环境变量 GEMINIAPIKEY 中填写你的 Gemini API 密钥 - [可选] 环境变量 BASEURL 中填写代理地址，例如 https://lingxi-pro

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence.

Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.

Google's coding-agent CLI running Gemini models. Terminal-based, supports MCP servers, and integrates with the Google Cloud agent stack.

Built by Matious — We build custom AI tools and MCP servers for businesses. Managing Google Ad Manager is tedious. Creating campaigns, uploading creatives, and configuring line items involves countless clicks through a complex UI. This MCP server changes that. Connect it to Claude and manage your entire ad operations through conversation: - "Create a new campaign for Nike ending December 31st" - "

Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.

mcp-ragchat An MCP server that adds RAG-powered AI chat to any website. One command from Claude Code. Tell Claude Code "add AI chat to mysite.com" and it will crawl your content, build a local vector store, spin up a chat server, and hand you an embed snippet. No cloud infra. No database. Just one API key. 1. Clone and build 2. Configure Claude Code (~/.claude/mcp.json) Open Claude Code and say: C

Give any AI the ability to build, validate, and deploy production multi-agent systems. This is an MCP server that connects AI assistants — ChatGPT, Claude, Gemini, Copilot, Cursor, Windsurf, and any MCP-compatible environment — directly to the ADAS platform. An AI developer says "Build me a customer support system with order tracking and escalation" — and their AI assistant handles the entire life

Seamlessly integrate Wolfram Alpha into your chat applications. This project implements an MCP (Model Context Protocol) server designed to interface with the Wolfram Alpha API. It enables chat-based applications to perform computational queries and retrieve structured knowledge, facilitating advanced conversational capabilities. Included is an MCP-Client example utilizing Gemini via LangChain, dem

Drive four external coding CLIs — Google's Antigravity (Gemini 3.6 Flash), OpenAI Codex, the GitHub Copilot CLI, and Cursor — as sub-agents inside Claude Code. Text answers, image generation, real repo work, and parallel swarms, on quota you already pay for. One MCP server, four backends. It exposes Google Antigravity, OpenAI Codex, the GitHub Copilot CLI, and Cursor to Claude Code as clean MCP to

Generate short video clips (with synchronized audio) and still images via the Omni Flash API (https://omniflash.net/) — Google's Gemini Omni Flash family. Use when the user asks to create a video or image from a prompt with Omni Flash, generate a short clip with sound, render an AI image with the Gemini Omni Flash models, or mentions seedance-2 / gpt-image-2 / nano-banana-2 in the context of Omni Flash.

Publish a website through the user's connected Shipvela account, inspect deployment status and logs, and return a verified live HTTPS URL. Use only when the user chooses Shipvela or asks to manage an existing Shipvela website.

ROS-MCP-Server connects large language models (such as Claude, GPT, and Gemini) with existing robots giving them bidirectional AI integration. With no changes to existing robot source code, this enables: - 🗣 Commanding the robot in natural language → instructions are translated into ROS/ROS2 commands. - 👀 Giving AI full visibility → subscribe to topics, call services, read sensor data, and monit

The first general-purpose sentiment analysis tool for AI agents. KeyNeg MCP Server brings enterprise-grade sentiment analysis to Claude, ChatGPT, Gemini, and any AI assistant that supports the Model Context Protocol (MCP). - 95+ Sentiment Labels - Comprehensive negative sentiment taxonomy - Keyword Extraction - Identify specific complaints and issues - Batch Processing - Analyze multiple texts eff

Build and publish websites through AI conversation. Create pages, upload assets, manage data, and deploy to custom domains — all from your favorite AI assistant. Just connect and start talking. 1. Open Le Chat → Intelligence → Connectors → + Add Connector 2. Choose Custom MCP Connector 3. Enter URL: https://mcp.websitepublisher.ai/ 4. Click Connect → Login → Done ✅ Add to your claudedesktopconfig.