Mcp AI Agent Skills

A Model Context Protocol (MCP) server that provides access to the full Massive.com financial data API through an LLM-friendly interface. Rather than exposing one tool per endpoint, this server gives the LLM four composable tools — search, docs, call, and query — that cover the entire Massive.com API surface. Data can be stored in-memory as DataFrames, queried with SQL, and enriched with built-in f

MCP server to look up domain names via rdap(1) and then whois(1). - Checkout the repo - build it: go build ./... - Point your MCP client at the binary:

An integration that allows LLMs to interact with Raindrop.io bookmarks using the Model Context Protocol (MCP). - Create bookmarks - Search bookmarks - Filter by tags - Node.js 16 or higher - Raindrop.io account and API token To install Raindrop.io Integration for Claude Desktop automatically via Smithery: 1. Clone the repository: 2. Install dependencies: 3. Set up environment variables: - Create a

MCP Server for the Giphy API, enabling AI models to search, retrieve, and utilize GIFs from Giphy. - Content Filtering: Filter results by rating (G, PG, PG-13, R) to ensure appropriate content - Optimized Response Format: Response data optimized for AI model consumption - Multiple Search Methods: Support for query-based, random, and trending GIF retrieval - Comprehensive Metadata: Each GIF comes w

Generates customer-ready roadmap views and launch timelines from ProductPlan for Sales and Customer Success teams. Use when preparing for customer calls, sharing product direction, or answering "when will feature X ship?" questions.

mcp.apify.com The Apify Model Context Protocol (MCP) server at mcp.apify.com enables your AI agents to extract data from social media, search engines, maps, e-commerce sites, and any other website using thousands of ready-made scrapers, crawlers, and automation tools from the Apify Store. It supports OAuth, allowing you to connect from clients like Claude.ai or Visual Studio Code using just the UR

Finally, MCP servers & commands that just work on Windows. Every MCP server README assumes macOS or Linux. You copy the config, paste it in, and nothing happens — because npx, uvx, and friends are .cmd batch shims on Windows, not real executables. mcp2win fixes this by wrapping commands with cmd.exe /c so your MCP servers actually start. Works with Claude Code/Desktop, VS Code, Cursor, Zed, Amazon

English | 日本語 mcp-alphabanana is a Model Context Protocol (MCP) server for generating image assets with Google Gemini. It is built for MCP-compatible clients and agent workflows that need fast image generation, transparent outputs, reference-image guidance, and flexible delivery formats. Keywords: MCP server, Model Context Protocol, Gemini AI, image generation, FastMCP Key capabilities: - Ultra-fa

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

Instead of manually checking the Rybbit dashboard, let your AI assistant query analytics data directly: - "How many users visited the site today?" - "Show me the top pages by bounce rate this week" - "What errors occurred in the last hour?" - "Show user journey from homepage to checkout" - "Compare browser usage between mobile and desktop" Or clone and build: Add to your ~/.claude/settings.json or

Scaffolds a new WebMCP tool component using useMcpTool with Zod schema, handler, annotations, and wires it into the WebMCPProvider tree. Use when the user wants to expose functionality as an MCP tool, make something callable by AI, add a new tool, or create an AI-accessible action.

13 production-ready tools for AI agents — one API key, zero complexity. Docs · Playground · OpenAPI Spec · npm Building AI agents that interact with the real world? You'd normally need: No credit card. No setup. 13 endpoints ready to use. Use Agent Toolbox as an MCP server in Claude Desktop, Cursor, or Windsurf: Add to Claude Desktop config: See MCP Quickstart Guide for full setup instructions. Al

Model Context Protocol server for OriginSelect — search ethical, origin-verified products and brands via AI agents. Works with Claude Desktop, Cursor, Windsurf, and any MCP-compatible client. No install needed — just add to your Claude Desktop config: Then add to Claude Desktop config: Add to your MCP settings: Once connected, ask your AI assistant: - "Find organic baby products from Canada under

- A minimal server/client application implementation utilizing the Model Context Protocol (MCP) and Azure OpenAI. 1. The MCP server is built with FastMCP. 2. Playwright is an an open source, end to end testing framework by Microsoft for testing your modern web applications. 3. The MCP response about tools will be converted to the OpenAI function calling format. 4. The bridge that converts the MCP

A Model Context Protocol server for the QA Sphere test management system. This integration enables Large Language Models (LLMs) to interact directly with QA Sphere test cases, allowing you to discover, summarize, and chat about test cases. In AI-powered IDEs that support MCP, you can reference specific QA Sphere test cases within your development workflow. - Node.js (recent LTS versions) - QA Sphe

This is a Model Context Protocol (MCP) server that integrates AgentQL's data extraction capabilities. - extract-web-data - extract structured data from a given 'url', using 'prompt' as a description of actual data and its fields to extract. To use AgentQL MCP Server to extract data from web pages, you need to install it via npm, get an API key from our Dev Portal, and configure it in your favorite

remotely attestable MCP server This project contains an MCP Server that is remotely attestable by MCP clients. To achieve this, a trusted execution environment is used, which generates a certificate representing the currently-running code of the attestable-mcp-server. The attestable-mcp-server sends this certificate in the TLS handshake to an MCP client before connecting that proves the code it's

This repository contains an implementation of a Model Context Protocol (MCP) server for the Royal Spanish Academy (RAE) API. It allows language models to interact with RAE's dictionary and linguistic resources. Run the server with stdio transport (for integration with LLMs): Or run it as an SSE server: The MCP server exposes the following tools to LLMs: 1. search - Search RAE API for information -

MCP server for Pearch.AI: natural-language search over people and companies/leads (B2B). Use it from Cursor, Claude Desktop, VS Code, or any MCP-compatible client. - searchpeople — natural-language search for people (e.g. “software engineers in California with 5+ years Python”); returns candidates with optional insights and profile scoring. - searchcompanyleads — find companies and leads/contacts

An experimental and educational Ping-Pong server demonstrating MCP (Model Context Protocol) calls via FastAPI. - ✅ FastAPI/FastMCP backend for remote MCP calls through API endpoints or SSE - 🔄 MCP integration for command handling - 🔐 Thread-safe session management To install the dependencies, run: Start the FastAPI server with: The server will start at http://localhost:8080. Open mcp-api-client.

MCP server implementation for Kibela API integration, enabling LLMs to interact with Kibela content. - Search notes with advanced filters - Get your latest notes - Get note content and comments - Manage groups and folders - Like/unlike notes - List users - View note attachments - View recently viewed notes - Get notes by path - KIBELATEAM: Your Kibela team name (required) - KIBELATOKEN: Your Kibel

The Web, Readable. Your AI agent spends 60,000 tokens just to look at a web page. Charlotte does it in 336. Charlotte is an MCP server that gives AI agents structured, token-efficient access to the web. Instead of dumping the full accessibility tree on every call, Charlotte returns only what the agent needs: a compact page summary on arrival, targeted queries for specific elements, and full detail

A lightweight, zero-config MCP server for documentation projects. Give it an llms-full.txt file (local path or URL) and optional OpenAPI/AsyncAPI directories. It also hellps you to build one if you do not have it. It registers only the MCP tools that make sense for what you've provided — no code changes, no hard-coded paths. - Why it's different - When to use this — and when not to - How it works

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