The financial data query skill based on Oriental Fortune's authoritative database and real-time market data supports natural language query of market, financial, relationship and business information, avoiding the use of outdated or inaccurate financial data in the model.
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Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install mx-dataOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install mx-dataβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/mx-data/π‘Extract and place the folder at the path above, then restart your agent.
Category
πData & AnalyticsPlatforms
What Mx Data can do for your AI workflow
Financial data query skill directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 1,155+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Mx Data
Help me get started with Mx Data
Explains what Mx Data does, walks through the setup, and runs a quick demo based on your current project
Use Mx Data to the financial data query skill based on Oriental Fortune's authorit...
Invokes Mx Data with the right parameters and returns the result directly in the conversation
What can I do with Mx Data in my data & analytics workflow?
Lists the top use cases for Mx Data, with example commands for each scenario
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Mx Data extends your AI assistant with the ability to the financial data query skill based on Oriental Fortune's authoritative database and real-time market data supports natural language query of market, financial, relationship and business information, avoiding the use of outdated or inaccurate financial data in the model. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Mx Data as its underlying capability.
Mx Data works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Mx Data once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Getting started with Mx Data takes about two minutes. Place the skill at `~/.claude/skills/mx-data/` (personal, all projects) or `.claude/skills/mx-data/` (project-specific), then restart your AI client. From that point, typing `/mx-data` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
Mx Data has been installed 1,155 times, making it one of the more actively used skills in the Data & Analytics category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/mx-data/ for personal use (all projects), or .claude/skills/mx-data/ for project-specific use. Restart your AI client, then invoke with /mx-data or let the AI discover it automatically.
Mx Data supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Mx Data is free to install. Check the repository for licensing information.
The financial data query skill based on Oriental Fortune's authoritative database and real-time market data supports natural language query of market, financial, relationship and business information, avoiding the use of outdated or inaccurate financial data in the model.
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