fintools-mcp
Provides a comprehensive financial analysis toolkit for AI assistants, featuring technical indicators, options chain analysis, and risk-based position sizing. It enables users to perform stock market analysis and evaluate trade performance using real-time data from Yahoo Finance.
README
fintools-mcp
Financial analysis tools for AI assistants via MCP (Model Context Protocol).
Give Claude, ChatGPT, Cursor, or any MCP-compatible AI access to real financial analysis — not just stock prices, but the analytical toolkit a trader actually uses.
Tools
| Tool | What it does |
|---|---|
get_technical_indicators |
RSI, MACD, ATR, EMAs (9/21/50/200), Fibonacci levels, trend assessment |
get_stock_quote |
Current price, volume, 52-week range, market cap |
analyze_options_chain |
Options chain with IV analysis, liquidity filtering, put/call ratios |
calculate_position_size |
Risk-based position sizing with stop loss and profit target |
calculate_atr_position |
ATR-based position sizing — auto-calculates stop and target from volatility |
analyze_trades |
Win rate, profit factor, Sharpe ratio, drawdown, streaks from trade P&Ls |
compare_tickers |
Side-by-side technical comparison across multiple symbols |
Quick Start
Install
pip install fintools-mcp
Or with uv:
uv pip install fintools-mcp
Add to Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"fintools": {
"command": "uv",
"args": ["run", "--from", "fintools-mcp", "fintools-mcp"]
}
}
}
Or if installed via pip:
{
"mcpServers": {
"fintools": {
"command": "fintools-mcp"
}
}
}
Add to Claude Code
claude mcp add fintools -- uv run --from fintools-mcp fintools-mcp
Examples
Once configured, you can ask your AI assistant things like:
- "What's the technical setup on AAPL right now?"
- "Analyze the SPY options chain for next Friday"
- "If I want to go long NVDA with a $100k account risking 1.5%, how many shares and where's my stop?"
- "Compare AAPL, GOOGL, MSFT, and AMZN — which has the strongest trend?"
- "Here are my last 20 trades: [150, -80, 200, ...] — what's my win rate and Sharpe?"
Example Output
Technical Indicators
> "What's the technical setup on SPY?"
SPY @ $573.42
RSI(14): 58.3 — bullish momentum
MACD: 2.14 (histogram +0.38, bullish)
ATR(14): $7.82
EMAs: 9 > 21 > 50 > 200 (fully stacked bullish)
Fibonacci: In golden pocket (0.618-0.65 retracement)
Trend: Bullish (all signals aligned)
Position Sizing
> "Size a long position on AAPL at $227, stop $220, target $245"
Shares: 214
Position value: $48,578
Risk: $1,498 (1.5% of $100k)
Reward: $3,852
R:R ratio: 2.57
Architecture
fintools-mcp/
├── fintools_mcp/
│ ├── server.py # MCP server — tool definitions
│ ├── data.py # Market data via yfinance
│ ├── indicators/ # Technical indicators (standalone, no deps)
│ │ ├── rsi.py # RSI — Wilder's smoothing
│ │ ├── macd.py # MACD (12, 26, 9)
│ │ ├── atr.py # ATR — Average True Range
│ │ ├── ema.py # EMA — any period
│ │ ├── vwap.py # VWAP — intraday, daily reset
│ │ └── fibonacci.py # Fibonacci retracement + golden pocket
│ └── analysis/
│ ├── position_sizer.py # Risk-based + ATR-based sizing
│ └── trade_stats.py # KPI calculator (60+ metrics)
└── tests/
Data Sources
- Stock data: Yahoo Finance (free, no API key required)
- Options data: Yahoo Finance options chains
- No API keys needed for basic functionality.
Development
git clone https://github.com/slimbiggins007/fintools-mcp.git
cd fintools-mcp
uv sync
uv run python -m fintools_mcp # starts the MCP server
Run tests:
uv run pytest
License
MIT
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.