FinSight
An AI-powered financial analyst MCP server that enables stock performance analysis, company comparison, and market trend interpretation directly in your IDE using local AI.
README
FinSight: AI-Powered Financial Analyst 📈
FinSight is an autonomous financial analysis agent that integrates directly into your IDE via the Model Context Protocol (MCP). Built with CrewAI and Deepseek-R1, it analyzes stock market data, fetches historical prices, and provides intelligent financial insights right where you work.
Instead of switching back and forth between financial websites and your code, you can just ask your IDE to analyze stock performance, compare companies, and interpret market trends.
🚀 Features
- Local AI Execution: Uses Deepseek-R1 via Ollama to keep your analysis private and local.
- Multi-Agent Orchestration: Powered by CrewAI to break down complex financial queries into specialized agent tasks.
- IDE Integration: Runs natively as an MCP server in Cursor or any compatible IDE.
- Real-Time Data: Fetches stock prices, volume, and trends using
yfinance.
🛠️ Getting Started
1. Prerequisites
- Python 3.11+
- Docker (Required by CrewAI for secure code execution)
- Ollama (For running Deepseek-R1 locally)
2. Install & Run Ollama
You'll need Ollama running in the background with the Deepseek-R1 model:
ollama run deepseek-r1
3. Install Dependencies
This project uses uv for fast dependency management.
uv sync --python 3.11
4. Connect to Your IDE (Cursor)
To use FinSight directly from your IDE, you need to add it as an MCP server.
- Open your IDE settings and navigate to MCP.
- Add a new global MCP server with the following configuration:
{
"mcpServers": {
"financial-analyst": {
"command": "uv",
"args": [
"--directory",
"C:/absolute/path/to/FinSight",
"run",
"server.py"
]
}
}
}
- Restart or reload the MCP server in your IDE.
💡 How to Use It
Once connected, you can chat with your IDE and ask financial questions like:
- "Show me Tesla's stock performance over the last 3 months."
- "Compare Apple and Microsoft stocks for the past year."
- "Analyze the trading volume of Amazon stock for the last month."
The AI will spin up the necessary CrewAI agents, fetch the data, and deliver a comprehensive analysis!
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。