wealvest-ai
Enables AI-driven financial analysis including portfolio analysis, risk assessment, investment simulation, market intelligence, and report generation via NitroStudio.
README
๐ฐ WealVest AI
AI-powered financial analysis platform built with NitroStack MCP.
WealVest AI demonstrates how the Model Context Protocol (MCP) can power modular AI-driven financial tools for investment analysis, risk assessment, market intelligence, and report generation.
Project Status: ๐ง MVP Complete | Website Integration In Progress
๐ Overview
WealVest AI is an experimental financial intelligence platform built for the NitroStack MCP Hackathon.
The project exposes financial capabilities as MCP tools that can be executed from NitroStudio, showcasing how AI-powered financial workflows can be implemented using modular MCP architecture.
Current capabilities include:
- ๐ Portfolio Analysis
- โ ๏ธ Risk Assessment
- ๐ Investment Simulation
- ๐ Market Intelligence
- ๐ Financial Report Generation
๐ Tech Stack
Frontend
- React
- TypeScript
- Tailwind CSS
- Vite
Backend
- Node.js
- NitroStack MCP
Development Tools
- NitroStudio
- TypeScript
- npm
โ Current Status
Successfully Implemented
๐ Portfolio Analyzer
- Portfolio analysis workflow
- Financial input validation
- MCP Tool implementation
- Widget integration
- Portfolio insights
โ ๏ธ Risk Assessment
- Risk profile analysis
- Financial scoring
- Risk recommendations
- MCP integration
๐ Investment Simulator
- Investment projection
- Return estimation
- Future value calculation
- Financial simulations
๐ Market Intelligence
- Market trend analysis
- Industry insights
- AI-assisted summaries
๐ Report Generator
- Financial report generation
- Structured summaries
- Recommendation reports
๐ MCP Integration
- MCP Server
- Tool Registration
- Widget Registration
- NitroStudio Integration
- Modular Architecture
โ Working Features
| Feature | Status |
|---|---|
| React Frontend | โ |
| Tailwind UI | โ |
| MCP Server | โ |
| Portfolio Analyzer | โ |
| Risk Assessment | โ |
| Investment Simulator | โ |
| Market Intelligence | โ |
| Report Generator | โ |
| NitroStudio Integration | โ |
| Widget Rendering | โ |
| Financial Tool Execution (NitroStudio) | โ |
๐ง Currently Under Development
The following functionality is not yet implemented:
- Website โ MCP communication
- Backend API integration
- Direct tool execution from the website
- Persistent user accounts
- Database integration
- Authentication
- Real-time financial data
- Production deployment
๐ Architecture
React Website
โ
โ
(UI Components Only)
โ
โผ
NitroStudio (MCP Client)
โ
โผ
NitroStack MCP Server
โ
โโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโ
โ โ โ
โผ โผ โผ
Portfolio Risk Assessment Investment Simulator
โ
โผ
Market Intelligence
โ
โผ
Report Generator
โ ๏ธ Current Limitation
At present, the financial tools are executed through NitroStudio, which acts as the MCP client.
The React website currently provides the frontend interface but does not yet communicate with the MCP server.
This means:
- โ MCP tools work inside NitroStudio.
- โ Widgets render correctly in NitroStudio.
- โ The website cannot yet invoke MCP tools directly.
Backend integration between the website and the MCP server is planned for a future update.
๐ Future Roadmap
Phase 1 โ (Completed)
- MCP server
- Financial tools
- NitroStudio integration
- Widget implementation
- Modular architecture
Phase 2 ๐ง
- Backend API
- Website โ MCP integration
- Live financial analysis from the website
- User authentication
- Portfolio persistence
- Database support
Phase 3 ๐ฎ
- AI investment recommendations
- Portfolio optimization
- Historical tracking
- PDF report export
- Cloud deployment
- Multi-user collaboration
- Real-time market APIs
โถ๏ธ Getting Started
Clone the repository:
git clone https://github.com/rhll07/wealvest-ai.git
Move into the project:
cd wealvest-ai
Install dependencies:
npm install
Run the development server:
npm run dev
๐งช Demo
Current demonstrations are performed through NitroStudio, where all implemented MCP tools can be executed and tested.
Available demo tools:
- ๐ Portfolio Analyzer
- โ ๏ธ Risk Assessment
- ๐ Investment Simulator
- ๐ Market Intelligence
- ๐ Report Generator
๐ค Contributing
Contributions, feature suggestions, and bug reports are always welcome.
- Fork the repository
- Create a feature branch
- Commit your changes
- Open a Pull Request
๐ License
This project is licensed under the MIT License.
๐จโ๐ป Author
Rahul Krishna R
If you found this project helpful or interesting, consider giving it a โญ on GitHub!
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.