LLM & AI Agent Skills

The CockroachDB MCP Server is a natural language interface designed for LLMs and agentic applications to manage, monitor, and query data in CockroachDB. It integrates seamlessly with MCP (Model Content Protocol) clients, such as Claude Desktop or Cursor, enabling AI-driven workflows to interact directly with your database. - Cluster Monitoring - Database Operations - Table Management - Query Engin

Model Context Protocol server for YDB. It allows to work with YDB databases from any LLM that supports MCP. This integration enables AI-powered database operations and natural language interactions with your YDB instances. uvx, which is an allias for uv run tool, allows you to run various python applications without explicitly installing them. Below are examples of how to configure YDB MCP using u

The Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis. It integrates seamlessly with MCP (Model Content Protocol) clients, enabling AI-driven workflows to interact with structured and unstructured data in Redis. Using this MCP Server, you can ask questions like: - "Store the entire conversation in a stream" - "Cache th

           CentralMind Gateway: Create API or MCP Server in Minutes 🚀 Interactive Demo avialable here: https://centralmind.ai Simple way to expose your database to AI-Agent via MCP or OpenAPI 3.1 protocols. This will run for you an API: Which you can use inside your AI Agent: Gateway will generate AI optimized API. AI agents and LLM-powered applications need fas

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. - Vector-based documentation search and retrieval - Support for multiple documentation sources - Semantic search capabilities - Automated documentation processing - Real-time context augmentation f

Search and retrieve biomedical data — genes, variants, clinical trials, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. 15 sources including PubMed, ClinicalTrials.gov, ClinVar, OncoKB, Reactome, UniProt, PharmGKB, OpenFDA, Monarch. Use when asked about gene function, variant pathogenicity, trial matching, drug safety, resistance mechanisms, hereditary syndromes, or literature evidence.

A Model Context Protocol (MCP) server that provides access to the MongoDB Atlas API. This server wraps the mongodb-atlas-api-client package to expose MongoDB Atlas functionality through MCP tools. This MCP server exposes most of the mongodb-atlas-api-client surface as MCP tools. - userget — Get a database user by username - usergetall — List all database users - usercreate — Create a database user

An MCP server that gives AI assistants safe, read-only access to SQL Server databases. Every query is parsed into a full AST using Microsoft's official T-SQL parser — not regex — so comment injection, string literal tricks, and encoding bypasses are blocked at the syntax level. Prerequisite: .NET 10.0 runtime 2. Configure — create ~/.config/sqlaugur/appsettings.json (Linux/macOS) or %APPDATA%\sqla

CRUD operations for knowledge base docs — add, delete, update metadata, embed. Requires GNOSIS_MCP_WRITABLE=true.

A Model Context Protocol (MCP) server that provides agentic tools for interacting with the Trieve API. This server enables AI agents to search and interact with Trieve datasets through a standardized interface. - Search across Trieve datasets using semantic search - List and access dataset information - Support for both environment variables and command-line arguments - Built with TypeScript for t

- MCP Server: code-to-tree - Using code-to-tree - Configure MCP Clients - Building (Windows) - Building (macOS) The code-to-tree server's goals are: 1. Give LLMs the capability of accurately converting source code into AST(Abstract Syntax Tree), regardless of language. 2. One standalone binary should be everything the MCP client needs. These goals imply: 1. The underlying syntax parser should be v

Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Also handles MCP setup and configuration.

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

A tool similar to cloc, sloccount and tokei. For counting the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages. Goal is to be the fastest code counter possible, but also perform COCOMO calculation like sloccount, LOCOMO estimation for LLM-based development costs, estimate code complexity similar to cyclomatic complexity calculators and prod

Screenpipe brand style guide. Reference this when designing UI components, writing copy, or making visual decisions.

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

MCP Server for the Notion API, enabling LLM to interact with Notion workspaces. Additionally, it employs Markdown conversion to reduce context size when communicating with LLMs, optimizing token usage and making interactions more efficient. Here is a detailed explanation of the steps mentioned above in the following articles: - English Version: https://dev.to/suekou/operating-notion-via-claude-des

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

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.

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

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

>-

Use when auditing a codebase for semantic duplication - functions that do the same thing but have different names or implementations. Especially useful for LLM-generated codebases where new functions are often created rather than reusing existing ones.

Apple Health MCP Server Apple Health Data Exploration Connect your Apple Health data with any LLM that supports MCP. Talk to your data and get personalised insights. This demo shows how Claude uses the apple-health-mcp-server to answer questions about your data. Example prompts from the demo: - I would like you to help me analyze my Apple Health data. Let's start by analyzing the data types - chec