Market Insights Server
@jashchawla8
关于 Market Insights Server
暂无概览
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-jashchawla8": {
"command": "python",
"args": [
"spark_market_insights_server.py",
"--commodity",
"nickel"
]
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Market Insights Server?
Market Insights Server is a real-time commodity tracking system that uses Apache Spark, OpenAI GPT, and the MCP protocol to collect, process, and generate actionable market insights from Reddit, News APIs, and Yahoo Finance.
How to use Market Insights Server?
Install dependencies with pip install -r requirements.txt, then run python spark_market_insights_server.py --commodity "nickel" (or any other commodity). The server outputs cleaned text data, TF-IDF features, a GPT-4‑powered insight report, and a JSON export of insights.
Key features of Market Insights Server
- Real‑time data collection from Reddit, News APIs, and Yahoo Finance
- Scalable processing using Apache Spark (PySpark 3.5.0)
- Natural language insights powered by GPT‑4
- Configurable for any commodity market: energy, metals, agriculture, and more
- Built‑in dynamic configuration generation and subreddit discovery
- Ready for deployment with error handling, retries, and async collection
Use cases of Market Insights Server
- Generate daily market sentiment reports for a specific commodity
- Monitor supply‑chain disruptions (e.g., export bans) through Reddit and news sentiment
- Combine price feeds with narrative analysis to anticipate price trends
- Support trading or investment decisions with AI‑summarized insights
FAQ from Market Insights Server
What Python version is required?
Python 3.x is required, with PySpark 3.5.0 and other dependencies listed in requirements.txt.
What data sources does Market Insights Server use?
It collects data from Reddit (via async scraping), News APIs, and Yahoo Finance for live price feeds.
How does the AI insight layer work?
It uses OpenAI GPT‑4 to summarize and synthesize market narratives into a human‑readable report.
What should I do if Spark stages get stuck?
Check memory settings and repartition the input; the README also notes this in the troubleshooting section.
Are there any plans for additional data sources?
Yes, YouTube video analysis and a public dashboard on Smithery.ai are listed as coming soon.
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