Gemini AI Agent Skills

A powerful Model Context Protocol (MCP) server that provides AI-powered image and video analysis using Google Gemini and Vertex AI models. - Dual Provider Support: Choose between Google Gemini API and Vertex AI - Multimodal Analysis: Support for both image and video content analysis - Flexible File Handling: Upload via multiple methods (URLs, local files, base64) - Storage Integration: Built-in Go

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

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.

Your AI keeps breaking things you told it not to touch. SpecLock makes it stop. Website · npm · Smithery · GitHub Developed by Sandeep Roy · Free & Open Source (MIT License) 100/100 on Claude's independent test suite. 929 tests across 18 suites. 0 false positives. 15.7ms per check. Gemini Flash hybrid, Spec Compiler, Code Graph, Typed Constraints, Python SDK, ROS2 integration. That's it. One c

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

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

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.

Your MCPs, supercharged. Find any tool instantly, execute with code mode, run on schedule, discover skills, load Photons, ready for any client. Smart loading saves tokens and energy. Instead of your AI juggling 50+ tools scattered across different MCPs, NCP gives it a single, unified interface with code mode execution, scheduling, skills discovery, and custom Photons. Your AI sees just 2-3 simple

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

A Model Context Protocol (MCP) server that enables you to manage Gitea/Forgejo repositories through AI assistants like Claude, Gemini, and Copilot. If you want to: - Smart progress tracking: Let AI help you track project progress and analyze bottlenecks - Automated issue categorization: Automatically tag issue labels and set milestones based on content - Priority sorting: Let AI analyze issue cont

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

MCP Unity is an implementation of the Model Context Protocol for Unity Editor, allowing AI assistants to interact with your Unity projects. This package provides a bridge between Unity and a Node.js server that implements the MCP protocol, enabling AI agents like Cursor, Windsurf, Claude Code, Codex CLI, GitHub Copilot, and Google Antigravity to execute operations within the Unity Editor. MCP Unit

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

When the user wants to create or update a README.md file for a project. Also use when the user says "write readme," "create readme," "document this project," "project documentation," or asks for help with README.md. This skill creates absurdly thorough documentation covering local setup, architecture, and deployment.

Automate GitHub workflows with AI assistance. Includes PR reviews, issue triage, CI/CD integration, and Git operations. Use when automating GitHub workflows, setting up PR review automation, creating GitHub Actions, or triaging issues.

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

Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript, com.google.genai:google-genai for Java, google.golang.org/genai for Go), model selection, and API capabilities.

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.

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

Multi-agent orchestration platform for enterprise AI development. Run 12+ AI agents concurrently with full governance, Gemini-powered code review, and enforced quality gates. Solves coordination, verification, and metrics challenges that stall enterprise AI adoption.