Python AI Agent Skills

A Model Context Protocol (MCP) server that provides local vector database functionality using FAISS for Retrieval-Augmented Generation (RAG) applications. - Local Vector Storage: Uses FAISS for efficient similarity search without external dependencies - Document Ingestion: Automatically chunks and embeds documents for storage - Semantic Search: Query documents using natural language with sentence

Access thousands of remote job listings and company information directly from your AI coding assistant! This public MCP server provides real-time access to Himalayas.app's remote job database. 🌐 Public Server URL: https://mcp.himalayas.app/sse Search for specific jobs using keywords with advanced filtering. Parameters: - keyword (string, optional): Search term (e.g., 'Python', 'React', 'Product M

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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 implementation that provides network control and management capabilities through the POX SDN controller. This server enables Python-based network programming, OpenFlow device management, and automated network analysis through POX's modular architecture. Perfect for educational environments, network prototyping, and SDN research. The server exposes two dynamic

IDA Pro Python scripting for reverse engineering. Use when writing IDAPython scripts, analyzing binaries, working with IDA's API for disassembly, decompilation (Hex-Rays), type systems, cross-references, functions, segments, or any IDA database manipulation. Covers ida_* modules (50+), idautils iterators, and common patterns.

The ArXiv MCP Server provides a bridge between AI assistants and arXiv's research repository through the Model Context Protocol (MCP). It allows AI models to search for papers and access their content in a programmatic way. 🤝 Contribute • 📝 Report Bug - 🔎 Paper Search: Query arXiv papers with filters for date ranges and categories - 📄 Paper Access: Download and read paper content - 📋 Paper Li

Best practices for building Stripe integrations

Stateful agent-to-agent communication client for the agent:// protocol. AGENIUM provides identity, discovery, and messaging for AI agents. Think of it as DNS + HTTP for agents — each agent gets a unique agent://name URI and can discover and communicate with other agents. Choose from 3 templates: echo (hello world), tools (tool-calling), api (REST gateway). - agent:// Protocol — Unique agent identi

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 Mattermost integration that connects to Model Context Protocol (MCP) servers, leveraging a LangGraph-based AI agent to provide an intelligent interface for interacting with users and executing tools directly within Mattermost. - 🤖 Langgraph Agent Integration: Uses a LangGraph agent to understand user requests and orchestrate responses. - 🔌 MCP Server Integration: Connects to multiple MCP serve

Initialize Claude Code framework infrastructure for any project

Specialized skill for building production-ready Discord bots. Covers Discord.js (JavaScript) and Pycord (Python), gateway intents, slash commands, interactive components, rate limiting, and sharding.

Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.

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Control Android devices with AI through the Model Context Protocol DroidMind is a powerful bridge between AI assistants and Android devices, enabling control, debugging, and system analysis through natural language. By implementing the Model Context Protocol (MCP), DroidMind allows AI models to directly interact with Android devices via ADB in a secure, structured way. When used as part of an agen

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Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.

MCP server implementation for TiDB (serverless) database. - uv (Python package installer) Go tidbcloud.com to create a free TiDB database cluster Configuration can be provided through environment variables, or using .env: - TIDBHOST - TiDB host address, e.g. 'gateway01.us-east-1.prod.aws.tidbcloud.com' - TIDBPORT - TiDB port (default: 4000) - TIDBUSERNAME - Database username, e.g. 'xxxxxxxxxx.\ '

This project provides a Model Context Protocol (MCP) server wrapper around the esp-rainmaker-cli Python library. It allows MCP-compatible clients (like LLMs or applications such as Cursor, Claude Desktop, and Windsurf) to interact with your ESP RainMaker devices using the official CLI. The Model Context Protocol (MCP) is a standardized framework that enables AI systems to interact with external to

Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.

An open source MCP (Model Context Protocol) server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments. - Quick Start - Prerequisites - Installation - Usage Examples - Configuration - Available Tools - Architecture - How It Works - MCP Client Integration - Performance Considerations - Troubleshooting -

The dicom-mcp server enables AI assistants to query, read, and move data on DICOM servers (PACS, VNA, etc.). 🤝 Contribute • 📝 Report Bug • 📝 Blog Post 1 dicom-mcp provides tools to: 🔍 Query Metadata: Search for patients, studies, series, and instances using various criteria. 📄 Read DICOM Reports (PDF): Retrieve DICOM instances containing encapsulated PDFs (e.g., clinical reports) and extract

MetaTrader MCP Server Let AI assistants trade for you using natural language Features • Quick Start • Documentation • Examples • Support MetaTrader MCP Server is a bridge that connects AI assistants (like Claude, ChatGPT) to the MetaTrader 5 trading platform. Instead of clicking buttons, you can simply tell your AI assistant what to do: The AI understands your request and executes it on MetaTrader