LLM & AI Agent Skills

A Model Context Protocol server for generating charts using AntV. We can use this mcp server for chart generation and data analysis. This is a TypeScript-based MCP server that provides chart generation capabilities. It allows you to create various types of charts through MCP tools. You can also use it in Dify. - ✨ Features - 🎨 Skill Usage - 🚰 Run with SSE or Streamable transport - 🎮 CLI Options

Code-Graph-RAG parses a multi-language codebase with Tree-sitter, builds a knowledge graph of its structure in Memgraph, and lets you query, edit, and optimise that code in plain English. It works across a monorepo of mixed languages under one unified graph schema. - Ruby Support: Ruby joins the graph through a new pluggable ast-grep tier that adds a language from a single YAML pattern file, emitt

MCP skill for airtable. Provides 8 tools: ping, list_bases, search_bases, list_tables_for_base, get_table_schema, list_records_for_table, create_records_for_table, update_records_for_table

Query and analyze LLM traces with AI assistance. Ask Claude to find expensive API calls, debug errors, compare model performance, or track token usage—all from your IDE. An MCP (Model Context Protocol) server that connects AI assistants to OpenTelemetry trace backends (Jaeger, Tempo, Traceloop), with specialized support for LLM observability through OpenLLMetry semantic conventions. See it in acti

The Docker Hub MCP Server is a Model Context Protocol (MCP) server that interfaces with Docker Hub APIs to make them accessible to LLMs, enabling intelligent content discovery and repository management. Developers building with containers, especially in AI and LLM-powered workflows, often face inadequate context across the vast landscape of Docker Hub images. As a result, LLMs struggle to recommen

An MCP (Model Context Protocol) server that provides token-efficient access to OpenAPI (v3.0) and Swagger (v2.0) specifications via MCP Resource Templates. The primary goal of this project is to allow MCP clients (like Cline or Claude Desktop) to explore the structure and details of large OpenAPI specifications without needing to load the entire file into an LLM's context window. It achieves this

MCP (Model Context Protocol) server that brings deterministic tech stack recommendations to LLM clients like Claude, Cursor, Windsurf, and other MCP-compatible tools. Try it free — 8 tools work without an account, including a daily demo recommendation and MCP project kit. Add to ~/Library/Application Support/Claude/claudedesktopconfig.json (macOS) or %APPDATA%\Claude\claudedesktopconfig.json (Wind

This MCP (Model Context Protocol) server provides various tools to interact with dbt. You can use this MCP server to provide AI agents with context of your project in dbt Core, dbt Fusion, and dbt Platform. Read our documentation here to learn more. This blog post provides more details for what is possible with the dbt MCP server. We publish an experimental Model Context Protocol Bundle (dbt-mcp.m

Please use Alby MCP instead! This repository has been deprecated in favor of Alby MCP, which includes all the NWC tools along with additional Lightning tools. Connect a bitcoin lightning wallet to your LLM using Nostr Wallet Connect (NWC or NIP-47). This MCP server uses the official MCP TypeScript SDK If your agent supports SSE (e.g. N8N) or HTTP Streamable transports, you can connect to Alby's MC

A Deno monorepo containing packages for macOS Calendar access: - @wyattjoh/calendar - Core library for read-only macOS Calendar database access - @wyattjoh/calendar-mcp - Model Context Protocol (MCP) server for LLM integration - Search calendar events by title/summary - Get recent past events - Get upcoming events - Retrieve events within date ranges - Get today's events with conflict detection -

Transcribe MCP Automate your transcriptions with AI. Transcribe MCP instantly connects your account to assistants like Claude, Windsurf, Cursor, and more so they can automate tasks on your behalf. The Local Server can add local files for transcription and return result to your Assistant in seconds. - ⚡ Fast, lightweight and LLM-friendly. No special ASR models needed, no setup and fighting python p

Model Context Protocol (MCP) Server for Langfuse Prompt Management. This server allows you to access and manage your Langfuse prompts through the Model Context Protocol. Quick demo of Langfuse Prompts MCP in Claude Desktop (unmute for voice-over explanations): This server implements the MCP Prompts specification for prompt discovery and retrieval. - prompts/list: List all available prompts - Optio

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

� Migrate to MCP Platform • 💬 Discord Community • � Legacy Docs Zero-configuration deployment of production-ready MCP servers with Docker containers, comprehensive CLI tools, and intelligent caching. Focus on AI integration, not infrastructure setup. That's it! Your MCP server is running at http://localhost:8080 Perfect for: AI developers, data scientists, DevOps teams building with MCP. Deploy M

mcp-name: io.github.king-of-the-grackles/reddit-research-mcp AI-Powered Reddit Intelligence for Market Research & Competitive Analysis Version: 1.0.0 Turn Reddit's chaos into actionable insights. Dialog is your all-in-one Reddit intelligence platform for competitive analysis, market research, and customer discovery across 20,000+ active subreddits. This is the official MCP server powering Dialog -

A Model Context Protocol (MCP) server implementation that provides the LLM an interface for visualizing data using Vega-Lite syntax. The server offers two core tools: - Save a table of data agregations to the server for later visualization - name (string): Name of the data table to be saved - data (array): Array of objects representing the data table - Returns: success message - visualizedata - Vi

Every multi-step tool workflow burns an LLM round-trip per step. The agent calls tool A, waits, sends the full context back to the model, gets a decision to call tool B, calls it, sends everything back again. Each round-trip re-transmits 2K–10K tokens on what is essentially plumbing. For a session with 20 two-step workflows, that's 20 wasted model calls, ~100K wasted tokens, and 20–40 seconds of a

Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.

An MCP (Model Context Protocol) server that enables AI platforms to interact with YepCode's infrastructure. Run LLM generated scripts and turn your YepCode processes into powerful tools that AI assistants can use directly. - Seamless AI Integration: Convert YepCode processes into AI-ready tools with zero configuration - Real-time Process Control: Enable direct interaction between AI systems and yo

mem0-mcp-server wraps the official Mem0 Memory API as a Model Context Protocol (MCP) server so any MCP-compatible client (Claude Desktop, Cursor, custom agents) can add, search, update, and delete long-term memories. The server exposes the following tools to your LLM: All responses are JSON strings returned directly from the Mem0 API. There are three ways to use the Mem0 MCP Server: 1. Python Pack

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

This is a Model Context Protocol (MCP) server designed specifically for AI agents and LLM applications. It acts as a bridge between artificial intelligence systems and the comprehensive OpenStreetMap tagging knowledge base provided by the official @openstreetmap/id-tagging-schema library. Current Status: Production-ready MCP server, actively maintained and continuously improved. The service is dep

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

MCP server that fetches YouTube video transcripts and optionally summarizes them. - Fetch transcripts in multiple formats (text, JSON, SRT, WebVTT, pretty-print) - Summarize videos — returns transcript with instructions for the LLM to produce a summary - List available languages for any video's transcripts - Flexible URL parsing — accepts full YouTube URLs (youtube.com/watch?v=, youtu.be/, youtube