LLM & AI Agent Skills

The server uses the MCP protocol to share access to a local Home Assistant instance with an LLM application. A powerful bridge between your Home Assistant instance and Language Learning Models (LLMs), enabling natural language control and monitoring of your smart home devices through the Model Context Protocol (MCP). This server provides a comprehensive API for managing your entire Home Assistant

This project provides Model Context Protocol (MCP) for the Mifos X Ecosystem, enabling AI agents to access financial data and operations. Implementations is available in Java (Quarkus). Use the MCP Inspector to test and debug your server: This starts a local web UI to connect to your MCP server via STDIO or SSE. Prerequisites: JDK 21+, Maven 1. Configure environment variables in your shell or IDE:

A powerful Ghidra extension that provides an MCP (Model Context Protocol) server, enabling AI assistants and other tools to interact with Ghidra's reverse engineering capabilities through a standardized API. GhidrAssistMCP bridges the gap between AI-powered analysis tools and Ghidra's comprehensive reverse engineering platform. By implementing the Model Context Protocol, this extension allows exte

The Mermaid MCP Server enables AI assistants like GitHub Copilot, Claude, and custom LLM applications to generate professional architecture diagrams, flowcharts, sequence diagrams, and more using natural language. It provides a Model Context Protocol interface for seamless integration with AI coding assistants. - 🤖 AI-Powered Generation: Create diagrams using natural language with GitHub Copilot

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

An MCP server that provides safe access to your iMessage database through Model Context Protocol (MCP). This server is built with the FastMCP framework and the imessagedb library, enabling LLMs to query and analyze iMessage conversations with proper phone number validation and attachment handling. - macOS (required for iMessage database access) - Python 3.6+ Install all required dependencies: - fa

deco Studio Open-source · TypeScript-first · Deploy anywhere Open-source private AI workspace for organizations. decocms.com/studio Studio packages the infrastructure behind an internal AI rollout: model routing, MCP authentication, agent configuration, SSO, RBAC, audit logs, and usage accounting. Your teams get chat. You keep control. Under the hood it's one control plane for your AI agents — one

ntfy-me-mcp provides AI assistants with the ability to send real-time notifications to your devices through the ntfy service (either public or selfhosted with token support). Get notified when your AI completes tasks, encounters errors, or reaches important milestones - all without constant monitoring. The server includes intelligent features like automatic URL detection for creating view actions

Large Language Models (LLMs) have made incredible strides in code generation and developer productivity. However, they face a key limitation: they can only reliably use APIs and libraries they’ve seen during training. This creates a bottleneck for adopting new tools, SDKs, or internal APIs — LLMs simply don’t know how to use them effectively. While tools can be given source code access (when inter

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augmented.

Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task.

The memory system for AI coding agents. Decisions, lessons, and context that persist across sessions. mcp-name: io.github.omega-memory/omega-memory AI coding agents are stateless. Every new session starts from zero. - Context loss. Agents forget every decision, preference, and architectural choice between sessions. Developers spend 10-30 minutes per session re-explaining context that was already e

An MCP server for Timeplus. generatesql to give LLM more knowledge about how to query Timeplus via SQL - Execute SQL queries on your Timeplus cluster. - Input: sql (string): The SQL query to execute. - By default, all Timeplus queries are run with readonly = 1 to ensure they are safe. If you want to run DDL or DML queries, you can set the environment variable TIMEPLUSREADONLY to false. listdatabas

An MCP server implementation that integrates the SearXNG API, providing web search capabilities. - Web Search: General queries, news, articles, with pagination. - URL Content Reading: Advanced content extraction with pagination, section filtering, and heading extraction. - Intelligent Caching: URL content is cached with TTL (Time-To-Live) to improve performance and reduce redundant requests. - Pag

A Model Context Protocol (MCP) server for querying NIST National Vulnerability Database (NVD) API endpoints. This MCP server exposes tools to query the NVD/CVE REST API and return formatted text results suitable for LLM consumption via the MCP protocol. It includes automatic query chunking for large date ranges and parallel processing for improved performance. Base API docs: https://nvd.nist.gov/d

An MCP server (stdio transport) that wraps Hugging Face's LocalPythonExecutor (from the smolagents framework). It is a custom Python runtime that provides basic isolation/security when running Python code generated by LLMs locally. It does not require Docker or VM. This package allows to expose the Python executor via MCP (Model Context Protocol) as a tool for LLM apps like Claude Desktop, Cursor

Chroma - the open-source embedding database . The fastest way to build Python or JavaScript LLM apps with memory! The Model Context Protocol (MCP) is an open protocol designed for effortless integration between LLM applications and external data sources or tools, offering a standardized framework to seamlessly provide LLMs with the context they require. This server provides data retrieval capabili

-brightgreen) A Model Context Protocol (MCP) server for analyzing technical debt across multiple programming languages. Designed to integrate with GitHub Copilot and other MCP-compatible tools. - Multi-language support: JavaScript, TypeScript, Python, Java, Swift, Kotlin, Objective-C, C++, C, C, Go, Rust, Ruby, PHP - Comprehensive analysis: Detects various types of tech debt including code quality

An MCP server that provides tools for checking latest stable package versions from multiple package registries: - npm (Node.js/JavaScript) - PyPI (Python) - Maven Central (Java) - Go Proxy (Go) - Swift Packages (Swift) - AWS Bedrock (AI Models) - Docker Hub (Container Images) - GitHub Container Registry (Container Images) - GitHub Actions This server helps LLMs ensure they're recommending up-to-da

An MCP (Model Context Protocol) server that provides tools for querying OCI registries and image references. This project implements an SSE-based MCP server that allows LLM-powered applications to interact with OCI registries. It provides tools for retrieving information about container images, listing tags, and more. - Get information about OCI images - List tags for repositories - Get image mani

Alibaba Cloud Ops MCP Server is a Model Context Protocol (MCP) server that provides seamless integration with Alibaba Cloud APIs, enabling AI assistants to operate resources on Alibaba Cloud, supporting ECS, Cloud Monitor, OOS, OSS, VPC, RDS and other widely used cloud products. It also enables AI assistants to analyze, build, and deploy applications to Alibaba Cloud ECS instances. Smithery AI FC-

The Parallel Task MCP allows initiating deep research or task groups directly from your favorite LLM client. It can be a great way to get to know Parallel’s different APIs by exploring their capabilities, but can also be used as a way to easily do small experiments while developing production systems using Parallel APIs. Please read our MCP docs here for more details. The official installation ins

An AI coding assistant built in Rust that provides both command-line and graphical interfaces for autonomous code analysis and modification. Multi-Modal Tool Execution: Adapts to different LLM capabilities with pluggable tool invocation modes - native function calling, XML-style tags, and triple-caret blocks - ensuring compatibility across various AI providers. Real-Time Streaming Interface: Advan

⚡ Fully automated MCP server + JADX plugin built to communicate with LLM through MCP to analyze Android APKs using LLMs like Claude — uncover vulnerabilities, analyze APK, and reverse engineer effortlessly. Thanks to these wonderful people for their contributions ⭐ ljt270864457 LilNick0101 - Read The Docs is now live: https://jadx-ai-mcp.readthedocs.io/en/latest/ JADX-AI-MCP is a plugin for the JA