Enables the FinPilot AI agent to send executive reports and emails to stakeholders using Gmail's SMTP service.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@FinPilot AI Run a DCF valuation on Tesla and send the executive report to my email"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
FinPilot AI is a next-generation Model Context Protocol (MCP) server that transforms standard LLMs into autonomous investment bankers.
FinPilot AI: The Autonomous Investment Banking Agent with Rich MCP UI is an MCP (Model Context Protocol) server that extends AI assistants — like Claude, Cursor, and any MCP-compatible client — with new, real-world capabilities. It is built and deployed on Nitrostack, the fastest way to build, deploy, and share MCP apps.
Related MCP server: OpenInsider MCP
FinPilot AI is a next-generation Model Context Protocol (MCP) server that transforms standard LLMs into autonomous investment bankers. Unlike traditional financial data plugins that simply return raw JSON or text, FinPilot features a Multi-Agent Orchestrator that coordinates specialized sub-agents to fetch live market data, calculate fundamental ratios, run Discounted Cash Flow (DCF) valuations, and assess portfolio diversification.
What truly sets FinPilot apart is its Server-Driven UI architecture. Using NitroStack's widget system, FinPilot dynamically renders stunning, interactive, glassmorphism React micro-frontends directly inside the chat interface. Furthermore, FinPilot bridges the gap between analysis and action by automatically compiling its findings into executive reports and securely emailing them to stakeholders via a custom SMTP integration.
The Model Context Protocol (MCP) is an open standard that lets AI assistants securely connect to external tools, data sources, and services. Instead of being limited to what it was trained on, an AI model can call MCP servers to fetch live data, run actions, and integrate with real systems.
This project is one such MCP server. Learn more about building and shipping MCP apps at nitrostack.ai.
🔌 MCP-native — works with any MCP-compatible client (Claude, Cursor, and more)
🛠️ Tools, resources & prompts — exposes structured capabilities to AI agents
⚡ Deployed on Nitrostack — reliable, hosted, and instantly shareable
🔐 Secure by design — secrets stay in environment variables, never in code
🧩 Composable — combine with other MCP apps to build powerful AI workflows
🚀 Live MCP endpoint: https://finpilot-6a6d8635-rushd-srmist.app.nitrocloud.ai/mcp
Point your MCP client at the endpoint above to try it instantly. Prefer a hosted setup? Deploy your own in minutes on Nitrostack.
Node.js 18+ (or your project runtime)
An MCP-compatible client (Claude Desktop, Cursor, etc.)
git clone https://github.com/ShahzaadAhmed/MCP_project.git
cd MCP_project
npm installCopy the example environment file and add your own values:
cp .env.example .envEnsure you set the following environment variables if you want to enable the email-sending features:
GMAIL_USER=your_gmail_address
GMAIL_APP_PASSWORD=your_16_character_app_passwordnpm run startAdd this server to your MCP client configuration. A typical entry looks like:
{
"mcpServers": {
"finpilot": {
"url": "https://finpilot-6a6d8635-rushd-srmist.app.nitrocloud.ai/mcp"
}
}
}Restart your client and the tools from this MCP server will be available to your AI assistant.
Want to build and ship an MCP server like this one? Nitrostack lets you create, deploy, and host MCP apps in minutes — no infrastructure to manage.
👉 Start building: https://nitrostack.ai
🌙 Discover and share MCP projects with the community on r/mcptothemoon
🧰 Browse a growing catalog of MCP apps on Nitrostack
An MCP server implements the Model Context Protocol to expose tools, resources, and prompts that AI assistants can call. It lets an AI model take real actions and access live data.
FinPilot AI is a next-generation Model Context Protocol (MCP) server that transforms standard LLMs into autonomous investment bankers.
Any MCP-compatible client, including Claude Desktop and Cursor. New clients are adding MCP support regularly.
Use Nitrostack to build, deploy, and host MCP apps without managing infrastructure.
BFSI & FinTech · FinPilot AI: The Autonomous Investment Banking Agent with Rich MCP UI · MCP · Model Context Protocol · MCP server · MCP app · AI tools · AI agents · LLM tools · Claude MCP · Nitrostack · deploy MCP server · build MCP app
MIT © 2026
Built with ❤️ using the Model Context Protocol on Nitrostack. Share your MCP app on r/mcptothemoon.
Analyze the sector and asset class diversification of a given stock portfolio.
Inputs: holdings (required).
Perform basic arithmetic calculations
Inputs: a (required), b (required), operation (required).
Calculate and retrieve key financial ratios like P/E, Debt-to-Equity, and ROE.
Inputs: ticker (required).
Convert temperature units based on file content or direct input. Supports Celsius (C) and Fahrenheit (F).
Inputs: file_name (required), file_type (required), file_content (required), value, +2 more.
Emails an investment report to a specified address.
Inputs: ticker (required), emailAddress (required), reportContent (required).
Aggregates findings into a comprehensive AI investment report.
Inputs: ticker (required), summary (required), recommendation (required).
Retrieve the income statement, balance sheet, or cash flow statement for a company.
Inputs: ticker (required), statementType (required), period.
Retrieve real market news articles for a specific stock.
Inputs: ticker (required).
Assess the live risk profile of a company including beta.
Inputs: ticker (required).
Retrieve the current real-time stock price and historical data for a given ticker symbol.
Inputs: ticker (required), period.
Coordinates multiple agents (Market Data, Financials, Valuation) to produce a unified analysis of a stock.
Inputs: query (required), ticker (required).
Runs a Discounted Cash Flow (DCF) model to estimate the intrinsic value of a stock using live free cash flows.
Inputs: ticker (required), growthRate, discountRate.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 12 tools
The financial tools are largely distinct, but generate_investment_report and orchestrate_financial_analysis have overlapping purposes as both produce analysis output. The generic calculate and convert_temperature tools are clearly separate but irrelevant to finance.
Most financial tools follow a clear verb_noun pattern (e.g., get_stock_price, calculate_financial_ratios). However, 'calculate' and 'convert_temperature' break the pattern and are not thematically aligned, creating inconsistency.
With 12 tools, the count is within the ideal range for a specialized server. However, two utility tools are unnecessary padding for a financial analysis domain, making the set slightly less focused.
The core financial analysis workflow is well covered: market data, financials, ratios, valuation, risk, portfolio analysis, report generation, and emailing. Minor gaps exist, such as no direct tool for comparing companies, but the major lifecycle is present.
Production MCP server for US equity and options intelligence: real-time IV radar, Monte Carlo simulation, options pressure, strategy backtesting, AI prediction, pre-trade risk analysis, and automated stock research reports.
Financial data MCP server for Claude, ChatGPT, Cursor and Codex. Real-time stock quotes, financial statements, options flow, SEC filings, insider trades, 13F holdings, macro data and market news from gloom.sh, the open-source Bloomberg Terminal alternative.
The Octagon MCP server provides specialized AI-powered financial research and analysis by integrating with the Octagon Market Intelligence API. It enables users to analyze public market data (SEC filings, earnings transcripts, financial metrics, and stock data for 8000+ companies), private market data (3M+ companies, 500k+ funding rounds, 2M+ M&A/IPO transactions), and conduct deep research including web scraping capabilities. The server also features autonomous research agents that search hundreds of sources and return fully cited reports in approximately one minute.
MCP server for Financial Modeling Prep API with 250+ financial data tools
