FinBrain MCP 

Requires Python 3.10+

A Model Context Protocol (MCP) server that exposes FinBrain datasets to AI clients (Claude Desktop, VS Code MCP extensions, etc.) via simple tools. Backed by the official finbrain-python SDK (v2 API).

• Package name: finbrain-mcp

• CLI entrypoint: finbrain-mcp

• Documentation: finbrain.tech/integrations/mcp

Features

AI-Powered Price Predictions

Access FinBrain's machine learning price forecasts with daily (10-day) and monthly (12-month) horizons. Includes mean predictions with 95% confidence intervals.

News & Sentiment Analysis

Browse recent news articles for any ticker, or track aggregated daily sentiment scores over time. Screen news across all tracked stocks.

Alternative Data

• LinkedIn Metrics — Employee count and follower trends as company health indicators
• App Store Ratings — Mobile app performance data for consumer-facing companies
• Options Flow — Put/call ratios and volume to gauge market positioning
• Reddit Mentions — Ticker mention counts across subreddits, collected every 4 hours
• Government Contracts — U.S. government contract awards from USAspending.gov

Institutional & Insider Activity

• US Congress Trades — Stock transactions disclosed by House representatives and Senators
• Corporate Lobbying — Lobbying filings with registrant, income, expenses, and issue codes
• Insider Transactions — SEC Form 4 filings showing executive buys and sells
• Analyst Ratings — Wall Street coverage and price target changes

What you get

• ⚡️ Local MCP server (no proxying) using your own FinBrain API key

• 🧰 Tools (JSON by default, CSV optional) with paging

  • health

  • available_markets, available_tickers, available_regions

  • predictions_by_market, predictions_by_ticker

  • news_by_ticker, news_sentiment_by_ticker

  • app_ratings_by_ticker

  • analyst_ratings_by_ticker

  • house_trades_by_ticker, senate_trades_by_ticker

  • corporate_lobbying_by_ticker

  • insider_transactions_by_ticker

  • linkedin_metrics_by_ticker

  • options_put_call

  • reddit_mentions_by_ticker

  • government_contracts_by_ticker

  • recent_news, recent_analyst_ratings

  • screener_sentiment, screener_analyst_ratings, screener_news

  • screener_insider_trading, screener_house_trades, screener_senate_trades

  • screener_put_call_ratio, screener_linkedin, screener_app_ratings, screener_reddit_mentions, screener_government_contracts

• 🧹 Consistent, model-friendly shapes (we normalize raw API responses)

• 🔑 Multiple ways to provide your API key: env var, file

Install

Option A — Standard install (pip)

# macOS / Linux / Windows
pip install --upgrade finbrain-mcp

Option B — Dev install (editable)

# from repo root
python -m venv .venv
source .venv/bin/activate # Windows: .\.venv\Scripts\activate
pip install -e ".[dev]"

Keep pip (prod) and your venv (dev) separate to avoid path mix-ups.

Option C — Docker

# Build the image
docker build -t finbrain-mcp:latest .

# Run with your API key
docker run --rm -e FINBRAIN_API_KEY="YOUR_KEY" finbrain-mcp:latest

See DOCKER.md for detailed Docker usage instructions.

Configure your FinBrain API key

A) In your MCP client config (recommended / most reliable)

Put the key directly in the MCP server entry your client uses (Claude Desktop or a VS Code MCP ex

... View full README on GitHub