Stock Intelligence MCP
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., "@Stock Intelligence MCPShow me NVIDIA's stock chart for the last year"
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.
Stock Intelligence MCP
What are MCP Apps? An extension to the Model Context Protocol that lets MCP servers return interactive HTML interfaces — charts, forms, dashboards — rendered directly inside the AI conversation. Announced in the MCP Apps blog post, supported in Claude Desktop, ChatGPT, VS Code, and more. This project uses MCP Apps to render canvas-based financial charts with inline controls that let you adjust parameters without a new AI call.
How It Works
Two modes — visual charts or inline data:
"Show me" → AI uses
stock_app→ interactive chart with controls appears"What's the price of" → AI uses
stock_quote→ numbers in text
You: "Show me NVIDIA's stock chart for the last year"
AI calls: stock_app(symbol="NVDA", view="chart", period="1y")
→ Interactive candlestick chart with volume bars and hover crosshair.
Inline controls: switch between 1M/3M/6M/1Y/2Y/5Y and Candle/Line/Area
without making a new AI call.You: "Show me Apple's quarterly financials"
AI calls: stock_app(symbol="AAPL", view="financials")
→ Column chart of revenue, net income, gross profit.
Inline controls: switch between Income/Balance Sheet/Cash Flow,
Quarterly/Annual, and Column/Bar/Dual Axes/Table.You: "What's Tesla's price right now?"
AI calls: stock_quote(symbol="TSLA")
→ Text: "TSLA is trading at $248.50, up +2.3% today.
Market cap $789B, 52-week range $152–$299."You: "Is Microsoft undervalued?"
AI calls: stock_app(symbol="MSFT", view="valuation")
→ DCF gauge chart: intrinsic value vs current price, margin of safety.
Verdict: undervalued/overvalued/fairly valued.You: "Who's reporting earnings this week?"
AI calls: stock_earnings_calendar(days_ahead=7)
→ Text: "47 earnings reports this week: AAPL (Mon), GOOGL (Tue)..."Related MCP server: FinImpulse MCP Server
Quick Start
1. Double-click the .mcpb file
Open stock-intelligence-mcp.mcpb — Claude Desktop will prompt you to install it.

2. Add your FMP API key
Get a free key (30 seconds): https://site.financialmodelingprep.com/developer/docs
Free tier: 250 API calls/day — enough for a full day of research. Claude Desktop will ask for it during setup.
3. Start asking
"Show me AAPL's stock chart as a line chart over 2 years"
"What are the latest analyst ratings for NVDA?"
"Show me Apple's balance sheet — annual view"
"Is Tesla undervalued or overvalued right now?"
"What's Amazon's earnings beat/miss record?"
"Who's reporting earnings this week?"
"What's the price of Google right now?"
"Show me today's market movers as a heatmap"
"Compare Apple's quarterly cash flow"
10 Tools
stock_app — Interactive Charting (1 tool, 7 views)
The AI picks the view based on your question. Each chart has inline controls to adjust parameters without a new AI call.
View | What it shows | Inline controls |
| Price history with volume | Period (1M–5Y), Style (Candle/Line/Area) |
| Live quote card with sparkline | — |
| Revenue, income, gross profit | Statement (Income/Balance/Cash Flow), Period (Q/Annual), Style |
| EPS actual vs estimate, beat/miss | Style (Card/Column/Table) |
| Rating donut, price targets, grades | Style (Card/Table) |
| DCF gauge, margin of safety | Style (Card/Table) |
| Top gainers/losers/most active | Style (Bar/Heatmap/Table) |
Inline Data Tools (7 tools — text responses)
Use these when you want numbers in text, not a visual chart. Every data tool has a chart equivalent.
Tool | What it returns | Chart equivalent |
| Price, change, volume, market cap, 52-week range |
|
| Historical daily OHLCV bars |
|
| Income/balance/cashflow statement data |
|
| EPS history, beat/miss record |
|
| Ratings, price targets, grade changes |
|
| DCF intrinsic value, margin of safety |
|
| Gainers, losers, most active |
|
Utility Tools (2 tools)
Tool | What it does |
| Find stocks by company name or keyword |
| Upcoming earnings dates and EPS estimates |
Architecture
stock_app (charting) Data tools (inline text)
──────────────────── ────────────────────────
User asks question User asks for numbers
→ AI picks view + params → AI picks data tool
→ Tool fetches from FMP API → Tool fetches from FMP API
→ Returns data with chart_type → Returns structured data
→ MCP App renders interactive chart → AI formats as text response
→ User adjusts with inline controls
→ Controls re-call stock_appAll charts are rendered with inline canvas — no external JS libraries. The HTML file is self-contained (~55KB) with 19 chart renderers.
Data Source
All data comes from Financial Modeling Prep (FMP) — free tier only:
What | Free tier? |
Real-time quotes | Yes — end-of-day data |
Historical charts | Yes — daily OHLCV |
Financial statements | Yes — income, balance sheet, cash flow |
Analyst data | Yes — ratings, price targets, grades |
DCF valuations | Yes — discounted cash flow models |
Market movers | Yes — gainers, losers, most active |
Earnings calendar | Yes — upcoming earnings dates |
Free tier: 250 API calls/day. One API key, takes 30 seconds to get one.
Rebuild the .mcpb
./build-mcpb.shOutputs a fresh stock-intelligence-mcp.mcpb. Double-click to reinstall.
Alternative: Run from source
pip install -e .
export FMP_API_KEY=your_key_here
stock-intelligence-mcpThen add to your Claude Desktop config (~/.claude/claude_desktop_config.json):
{
"mcpServers": {
"stock-intelligence": {
"command": "stock-intelligence-mcp",
"env": {
"FMP_API_KEY": "your_key_here"
}
}
}
}Hosted Version
Don't want to manage API keys or run locally?
mcpbundles.com — same tools, zero setup, 200+ FMP tools always available.
Contributing
PRs welcome — new chart types, data visualizations, UI improvements.
git clone https://github.com/thinkchainai/stock-intelligence-mcp.git
cd stock-intelligence-mcp
pip install -e .License
MIT — see LICENSE.
Built by MCPBundles.
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