Mcp AI Agent Skills

Generate mermaid diagram and chart with AI MCP dynamically. Also you can use: - mcp-server-chart to generate chart, graph, map. - Infographic to generate infographic, such as Timeline, Comparison, List, Process and so on. - Fully support all features and syntax of Mermaid. - Support configuration of backgroundColor and theme, enabling large AI models to output rich style configurations. - Support

AI can build products. But it still doesn't talk to users. Usercall MCP lets AI agents run user interviews via voice calls and return structured insights with themes and verbatim quotes. Works with Claude Desktop, Cursor, and any MCP-compatible client. AI agents can now build and ship products extremely quickly. But most agents still rely on synthetic feedback or assumptions about users. Usercall

A Model Context Protocol server for Zotero integration. It gives any LLM full access to your Zotero library: search, organize, add papers by DOI, import PDFs, read full-text content, and inject live citations into Word documents. The server is designed to be usable by any LLM without external documentation. On connection, it sends workflow instructions via the MCP instructions field, and each tool

MetaMCP is a MCP proxy that lets you dynamically aggregate MCP servers into a unified MCP server, and apply middlewares. MetaMCP itself is a MCP server so it can be easily plugged into ANY MCP clients. For more details, consider visiting our documentation site: https://docs.metamcp.com English | 中文 - 🎯 Use Cases - 📖 Concepts - 🖥️ MCP Server - 🔐 Environment Variables \& Secrets (STDIO MCP Serve

An MCP server that triangulates customer support tickets and feature requests to help PMs decide what to build next. - Signal triangulation — Not just data access. Matches support tickets against feature requests to find convergent themes, then scores them with a weighted formula that gives convergent signals a 2x priority boost. - Composability — Designed to work with other MCP servers. Pass chur

An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data. - osm-mcp-server: The main server, available for public use. This server provides LLMs with tools to interact with OpenStreetMap data, enabling location-based applications to: - Geocode addresses and place names to coordinates - Reverse geocode coordinates to addresses - Find

THE PROJECT HAS BEEN SPLIT AND MOVED TO INDIVIDUAL REPOSITORIES. - Google Kit: Tools for Gmail, Google Calendar, Google Chat - RAG Kit: Tools for RAG, Memory - Dev Kit: Tools for developers, jira, confluence, gitlab, github, ... - Fetch Kit: Tools for fetch, scrape, ... - Research Kit: Tools for research, academic, reasoning, ... A powerful Model Context Protocol (MCP) server implementation with i

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

An MCP server for JupyterCAD that allows you to control it using LLMs/natural language. Suggestions and contributions are very welcome. The default transport mechanism is stdio. To start the server with stdio, use the following command: To use the streamable-http transport, use this command instead: An example using the OpenAI Agents SDK is available at examples/openaiagentsclient.py. To run it, f

Agent Skill Loader is a Model Context Protocol (MCP) server that acts as a bridge between your static Claude Code Skills library and dynamic AI agents (like Antigravity, Claude Desktop, or Cursor). It allows agents to "learn" skills on demand without requiring you to manually copy files into every project. Discovery: listskills - Scans your configured skill directories. Dynamic Learning: readskill

The local Dynatrace MCP server allows AI Assistants to interact with the Dynatrace observability platform, bringing real-time observability data directly into your development workflow. If you need help, please contact us via GitHub Issues if you have feature requests, questions, or need help. You can add this MCP server to your MCP Client like VSCode, Claude, Cursor, Amazon Q, Windsurf, ChatGPT,

日本語版 README はこちら Translation quality evaluation MCP Server powered by xCOMET (eXplainable COMET). xCOMET MCP Server provides AI agents with the ability to evaluate machine translation quality. It integrates with the xCOMET model from Unbabel to provide: - Quality Scoring: Scores between 0-1 indicating translation quality - Error Detection: Identifies error spans with severity levels (minor/major/c

MCP Server that enables LLMs to interact with the local filesystem. Provides tools for navigation, search, file management, and analysis — all scoped to allowed directories. Filesystem MCP exposes a rich set of tools for reading, writing, searching, and inspecting files and directories. All operations are strictly bounded to the directories you provide at startup, preventing access to any path out

Give any AI the ability to build, validate, and deploy production multi-agent systems. This is an MCP server that connects AI assistants — ChatGPT, Claude, Gemini, Copilot, Cursor, Windsurf, and any MCP-compatible environment — directly to the ADAS platform. An AI developer says "Build me a customer support system with order tracking and escalation" — and their AI assistant handles the entire life

Analyze AWS infrastructure security using Cyntrisec MCP tools. Use when asked about AWS attack paths, security findings, IAM permissions, compliance status, or remediation recommendations. Guides tool selection and workflow patterns for comprehensive security assessments.

A Model Context Protocol (MCP) server implementation for Azure DevOps, allowing AI assistants to interact with Azure DevOps APIs through a standardized protocol. This server implements the Model Context Protocol (MCP) for Azure DevOps, enabling AI assistants like Claude to interact with Azure DevOps resources securely. The server acts as a bridge between AI models and Azure DevOps APIs, providing

- 🎯 Quick Start - Become an x402 Champion - 📚 Official Resources - 📖 Protocol Documentation - 🚀 Quickstart Guides - ⚙️ Protocol Implementations - 🏭 Production Implementations - 🛠️ SDKs & Client Libraries - 🔧 Server Frameworks & Middleware - 🏗️ Facilitators - 💡 Example Applications - 🎨 Use Cases & Patterns - 🤖 AI Agent Integration - 🔨 Tools & Utilities - 🧪 Testing & Development - 📚 Tu

A Model Context Protocol (MCP) server for the Discord API (JDA), allowing seamless integration of Discord Bot with MCP-compatible applications like Claude Desktop. Enable your AI assistants to seamlessly interact with Discord. Manage channels, send messages, and retrieve server information effortlessly. Enhance your Discord experience with powerful automation capabilities. Manual Installation M

A high-performance Model Context Protocol (MCP) server for Trino implemented in Go. This project enables AI assistants to seamlessly interact with Trino's distributed SQL query engine through standardized MCP tools. This project implements a Model Context Protocol (MCP) server for Trino in Go. It enables AI assistants to access Trino's distributed SQL query engine through standardized MCP tools. T

A Model Context Protocol (MCP) server that enables Claude Desktop (and other MCP clients) to generate images, videos, music, and audio using Fal.ai models. - Native Async API - Uses falclient.runasync() for optimal performance - Queue Support - Long-running tasks (video/music) use queue API with progress updates - Non-blocking - All operations are truly asynchronous - STDIO - Traditional Model Con

A comprehensive Model Context Protocol (MCP) server that provides Claude Desktop and other MCP clients with tools for Kafka Schema Registry operations. Features advanced schema context support, multi-registry management, and comprehensive schema export capabilities. Latest Version: v2.1.5 | Docker: aywengo/kafka-schema-reg-mcp:stable - 🚀 Quick Start - ✨ Key Features - 🛠️ Claude Code Skills - 📦

Cal Server 是一个基于 FastMCP 框架构建的简单数学表达式计算服务，使用 Bun 运行时环境。它利用 expr-eval 库解析和计算用户输入的数学表达式，并通过标准输入输出（stdio）与外界交互。该项目旨在提供一个轻量、高效的计算工具，支持基本数学运算和内置常量。 - 表达式计算：支持用户输入数学表达式并返回计算结果。 - E：Bun 环境中的 Math.E。 - PI：Bun 环境中的 Math.PI。 - true：逻辑真值。 - false：逻辑假值。 - 工具名称：cal。 - 参数：接受一个字符串类型的数学表达式（exp）。 - fastmcp：用于构建 MCP 服务。 - expr-eval：用于解析和计算数学表达式。 - zod：用于参数验证。 - 确保已安装 Bun 运行时（推荐最新版本）。 To install cal-mcp for Claude D

A Model Context Protocol (MCP) server for interacting with Twitter. To install Twikit Twitter Search for Claude Desktop automatically via Smithery: Using mcp-client-cli

This project provides a FastMCP server for mathematical computations, including numerical and symbolic calculations, as well as plotting. - Python 3.12 or higher (To install Python3.12 follow Python Download) - uv (To install uv follow uv Installation) You can find the mcp.json file in the MCP: Open User Configuration or MCP: Open Workspace Configuration Add the following to your mcp.json: If you'