Gemini AI Agent Skills

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

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

Stop copy-pasting between AI models. Roundtable AI is a local MCP server that lets your primary AI assistant delegate tasks to specialized models like Gemini, Claude, Codex, and Cursor. Solve complex engineering problems in parallel, directly from your IDE. Key Features: - Context Continuity: Shared project context across all sub-agents - Parallel Execution: All agents work simultaneously - Model

Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.

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.

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

Manage YouTube activities using the yutu CLI. Use this skill when you need to list channel activities such as uploads, likes, and favorites.

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

mcp-trinv-server (ou MCPTRINV) est un serveur de type MCP (Model Context Protocol) qui est utilisé pour augmenter les ressources d'assistant d'Intelligence Artificielle comme Claude ou Gemini. MCPTRINV permet de rechercher des communes à partir d'un fragment de leur nom puis de rechercher des parcelles cadastrales dans une commune ayant une surface donnée. Il s'appuie sur le site TRINV. - trinv-ch

An MCP (Model Context Protocol) server that provides unified access to multiple Large Language Model APIs for AI coding environments like Cursor and Claude Desktop. - 🌐 8 LLM Providers – ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, Mistral - 🎯 Smart Model Selection – Tag-based preferences (coding, business, reasoning, math, creative, general) - 📊 Prompt Logging – Track all prompts

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

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.

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.

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.

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.

MCP (Model Context Protocol) server for Nanana AI image generation service powered by Google Gemini's nano banana model. This server allows Claude Desktop and other MCP clients to generate and transform images using nano banana's powerful image generation capabilities. 1. Visit nanana.app and sign in 2. Go to your account dashboard 3. Generate an API token in the "API Access" section 4. Copy and s

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 local Model Context Protocol (MCP) server that provides structured, high-signal insight into a Git repository, enabling AI coding agents to understand project state, structure, activity, and risk — without uploading or modifying the codebase. AI coding agents (Claude Code, Cursor, Codex, Gemini, etc.) are powerful, but they lack situational awareness when working with non-trivial codebases. They

A Model Context Protocol (MCP) server for GitLab and Jira integration. This server allows AI agents like gemini-cli to interact with your GitLab and Jira instances. - Projects: List all accessible projects or filter them by name. - Merge Requests: List merge requests for a project, get detailed information (including diffs), add comments, and assign reviewers. - Pipeline/CI/CD: Get pipeline status

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

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

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

Write less code and say less about it. Honey (I Shrunk the AI) by GreenPT is a cross-tool coding skill that cuts AI coding-agent token usage and LLM API costs — making agents emit less code and less prose without losing correctness. It works with Claude (claude.ai and the API), Claude Code, Cursor, GitHub Copilot, Codex, Gemini CLI, Windsurf, Cline, OpenClaw, Kiro, and Kilo Code. Three independent

Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space syncing, and JSON output for automation.