mcp-finnhub
Click on "Install 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., "@mcp-finnhubGet the latest stock price for Apple."
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.
mcp-finnhub
Model Context Protocol (MCP) server providing comprehensive access to Finnhub financial market data API. Built for AI assistants like Claude Desktop to seamlessly access real-time market data, technical indicators, fundamentals, and alternative data.
Features
15 MCP Tools covering 100+ Finnhub API endpoints
Real-time market data: Quotes, candles, tick data, BBO
Technical analysis: 50+ indicators, patterns, support/resistance
Fundamentals: Financials, earnings, dividends, metrics
Alternative data: ESG scores, social sentiment, supply chain
Multi-asset support: Stocks, crypto, forex, ETFs, bonds
Project-based storage with automatic CSV/JSON exports
Background job processing for large datasets
Smart output handling with token estimation
Configurable tools - enable only what you need
AI-friendly errors - Structured error responses with guidance
Built-in help - Every tool supports
operation="help"for discovery
Quick Start
Prerequisites
Python 3.11 or higher
Finnhub API key (free tier available)
Claude Desktop or compatible MCP client
Installation
Option 1: Install from PyPI (coming soon)
pip install mcp-finnhubOption 2: Install from source
git clone https://github.com/cfdude/mcp-finnhub.git
cd mcp-finnhub
pip install -e .Configuration
Create a
.envfile in your project root:
# Required
FINNHUB_API_KEY=your_api_key_here
FINNHUB_STORAGE_DIR=/path/to/storage
# Optional - Tool configuration
FINNHUB_ENABLE_TECHNICAL_ANALYSIS=true
FINNHUB_ENABLE_STOCK_MARKET_DATA=true
FINNHUB_ENABLE_NEWS_SENTIMENT=true
# ... enable/disable other tools as needed
# Optional - Performance tuning
FINNHUB_RATE_LIMIT_RPM=300 # Requests per minute (30 free, 300 premium)
FINNHUB_REQUEST_TIMEOUT=30 # Request timeout in seconds
FINNHUB_SAFE_TOKEN_LIMIT=75000 # Conservative token limitConfigure Claude Desktop to use mcp-finnhub by adding to
claude_desktop_config.json:
{
"mcpServers": {
"finnhub": {
"command": "mcp-finnhub",
"env": {
"FINNHUB_API_KEY": "your_api_key_here",
"FINNHUB_STORAGE_DIR": "/Users/yourname/finnhub-data"
}
}
}
}Restart Claude Desktop
First Query
Ask Claude:
"Get me the latest quote for AAPL"
Claude will use the finnhub_stock_market_data tool with the get_quote operation to fetch Apple's real-time stock quote.
Available Tools
Core Trading & Analysis (3 tools)
finnhub_stock_market_data- Quotes, candles, tick data, BBO, market statusfinnhub_technical_analysis- 50+ indicators (RSI, MACD, SMA), patterns, signalsfinnhub_news_sentiment- Company news, market news, sentiment scores
Fundamentals & Analysis (5 tools)
finnhub_stock_fundamentals- Financials, earnings, dividends, metricsfinnhub_stock_estimates- Revenue/EPS estimates, price targetsfinnhub_stock_ownership- Insider trades, institutional holdingsfinnhub_alternative_data- ESG scores, social sentiment, supply chainfinnhub_sec_filings- SEC filings, earnings transcripts
Multi-Asset Data (4 tools)
finnhub_crypto_data- Crypto exchanges, symbols, profiles, candlesfinnhub_forex_data- Forex rates, candles, exchangesfinnhub_calendar_data- IPO calendar, earnings calendar, economic eventsfinnhub_market_events- Market holidays, analyst upgrades/downgrades
Management Tools (3 tools)
finnhub_project_create- Create project workspacesfinnhub_project_list- List all projects with statisticsfinnhub_job_status- Check background job status
Example Workflows
Technical Analysis Workflow
User: "Analyze TSLA using RSI and MACD indicators"
Claude uses:
1. finnhub_technical_analysis → get_indicator (operation=get_indicator, symbol=TSLA, indicator=rsi)
2. finnhub_technical_analysis → get_indicator (operation=get_indicator, symbol=TSLA, indicator=macd)
3. Analyzes both indicators and provides trading insightsFundamental Research Workflow
User: "Research MSFT - get financials, earnings, and analyst estimates"
Claude uses:
1. finnhub_stock_fundamentals → get_basic_financials (operation=get_basic_financials, symbol=MSFT)
2. finnhub_stock_fundamentals → get_earnings (operation=get_earnings, symbol=MSFT)
3. finnhub_stock_estimates → get_earnings_estimates (operation=get_earnings_estimates, symbol=MSFT)
4. Summarizes financial health and analyst outlookMulti-Asset Portfolio Workflow
User: "Create a project called 'my-portfolio', get quotes for AAPL, BTC-USD, and EUR/USD"
Claude uses:
1. finnhub_project_create → create (operation=create, project=my-portfolio)
2. finnhub_stock_market_data → get_quote (operation=get_quote, symbol=AAPL, project=my-portfolio)
3. finnhub_crypto_data → get_crypto_profile (operation=get_crypto_profile, symbol=BINANCE:BTCUSDT)
4. finnhub_forex_data → get_forex_rates (operation=get_forex_rates, base=EUR, project=my-portfolio)
5. All data saved to /storage/my-portfolio/ with CSV exportsTool Configuration
Control which tools are available to reduce context window usage:
# Disable tools you don't need
FINNHUB_ENABLE_CRYPTO=false
FINNHUB_ENABLE_FOREX=false
FINNHUB_ENABLE_ALTERNATIVE_DATA=false
# Core tools (always recommended)
FINNHUB_ENABLE_STOCK_MARKET_DATA=true
FINNHUB_ENABLE_TECHNICAL_ANALYSIS=true
FINNHUB_ENABLE_NEWS_SENTIMENT=trueRate Limits
Free tier: 60 requests/minute
Basic tier: 150 requests/minute ($49.99/month)
Premium tier: 300 requests/minute
Enterprise tier: Custom limits
mcp-finnhub automatically handles rate limiting with exponential backoff and retry logic.
AI Agent Features
Help/Discovery
Every tool supports operation="help" to discover available operations:
finnhub_stock_fundamentals(operation="help")
# Returns all operations with required/optional params and examplesStructured Errors
Errors return actionable JSON instead of stack traces:
{
"error": "invalid_operation",
"message": "Operation 'get_data' not found",
"valid_operations": ["get_basic_financials", "get_dividends", ...],
"tool": "finnhub_stock_fundamentals"
}Storage Structure
Projects are stored in subdirectories:
FINNHUB_STORAGE_DIR/
├── my-portfolio/
│ ├── .project.json # Project metadata
│ ├── candles/ # Historical price data
│ ├── quotes/ # Real-time quotes
│ ├── news/ # News articles
│ ├── fundamentals/ # Financial data
│ ├── technical/ # Technical indicators
│ └── jobs/ # Background job results
└── research-tech/
└── ...Development
Setup
# Clone repository
git clone https://github.com/cfdude/mcp-finnhub.git
cd mcp-finnhub
# Install with dev dependencies
pip install -e ".[dev]"
# Run tests
pytest --cov=mcp_finnhub --cov-report=term-missing
# Lint and format
ruff check --fix .
ruff format .Running Locally
# Set environment variables
export FINNHUB_API_KEY=your_api_key
export FINNHUB_STORAGE_DIR=/tmp/finnhub-data
# Run with STDIO transport (default, for Claude Desktop)
mcp-finnhub
# Run with HTTP streaming (recommended for persistent/remote connections)
mcp-finnhub --transport http --port 8000
# Run with SSE transport (deprecated, use HTTP instead)
mcp-finnhub --transport sse --port 8000
# Custom host binding for network access
mcp-finnhub --transport http --host 0.0.0.0 --port 8125Transport Options
Transport | Use Case | Command |
| Claude Desktop, local MCP clients |
|
| Remote connections, persistent server, Claude Code |
|
| Legacy SSE clients (deprecated) |
|
Running as a Persistent Service
For HTTP transport, you can run the server as a background service:
# Using nohup (simple)
nohup mcp-finnhub --transport http --port 8000 > finnhub.log 2>&1 &
# Using systemd (Linux)
# See docs/DEPLOYMENT.md for service file examplesTesting with MCP Inspector
# Install MCP inspector
npm install -g @modelcontextprotocol/inspector
# Test the server
mcp-inspector mcp-finnhubArchitecture
FastMCP Server: Built on MCP SDK's FastMCP for multi-transport support
ServerContext: Dependency injection container managing client and utilities
Multi-Transport: STDIO (default), HTTP streaming, and SSE transports
Async Job Processing: Background workers for large dataset operations
Type Safety: Pydantic models for all API requests/responses
See ARCHITECTURE.md for detailed design documentation.
API Reference
See API.md for complete tool documentation with examples.
Troubleshooting
"Authentication failed" error
Verify your
FINNHUB_API_KEYis correctCheck if your API key has expired
Ensure you haven't exceeded rate limits
"Tool not found" error
Check that the tool is enabled in your configuration
Verify tool names match exactly (case-sensitive)
Storage permission errors
Ensure
FINNHUB_STORAGE_DIRexists and is writableCheck filesystem permissions
Rate limit errors
Reduce
FINNHUB_RATE_LIMIT_RPMin your configurationUpgrade to premium tier for higher limits
Contributing
Contributions welcome! Please:
Fork the repository
Create a feature branch
Add tests for new functionality
Ensure all tests pass
Submit a pull request
License
MIT License - see LICENSE for details
Acknowledgments
Built with Model Context Protocol
Powered by Finnhub API
Inspired by mcp-fred patterns
Support
Issues: GitHub Issues
Documentation: docs/
Finnhub API Docs: finnhub.io/docs/api
Made with ❤️ for the AI assistant ecosystem
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