Sponsored by Deepsite.site

MCP.so

FinBrain MCP

Created By
ahmetsbilgina month ago
Access institutional-grade alternative financial data directly in your LLM workflows.
# finance
# quant
OverviewContentToolsComments
Content

FinBrain MCP 

PyPI version CI License

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.

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

Track aggregated sentiment scores derived from financial news coverage. Monitor how market sentiment shifts over time for any ticker.

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

Institutional & Insider Activity

  • US Congress Trades — Stock transactions disclosed by House representatives and Senators
  • 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

    • predictions_by_market, predictions_by_ticker

    • news_sentiment_by_ticker

    • app_ratings_by_ticker

    • analyst_ratings_by_ticker

    • house_trades_by_ticker, senate_trades_by_ticker

    • insider_transactions_by_ticker

    • linkedin_metrics_by_ticker

    • options_put_call

  • 🧹 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 extension). This guarantees the launched server sees it, even if system env vars aren’t picked up.

Claude Desktop (pip install)

{
  "mcpServers": {
    "finbrain": {
      "command": "finbrain-mcp",
      "env": { "FINBRAIN_API_KEY": "YOUR_KEY" }
    }
  }
}

B) Environment variable

This works too, but note you must restart the client after setting it so the new value is inherited.

# macOS/Linux
export FINBRAIN_API_KEY="YOUR_KEY"

# Windows (PowerShell, current session)
$env:FINBRAIN_API_KEY="YOUR_KEY"

# Windows (persistent for new processes)
setx FINBRAIN_API_KEY "YOUR_KEY"
# then fully quit and reopen your MCP client (e.g., Claude Desktop)

Tip: If the env var route doesn’t seem to work (common on Windows if the client was already running), use the config JSON env method above—it’s more deterministic.

Run the server

Note: You typically don’t need to run the server manually—your MCP client (Claude/VS Code) starts it automatically. Use the commands below only for manual checks or debugging.

  • If installed (pip):

    finbrain-mcp

  • From a dev venv:

    python -m finbrain_mcp.server

Quick health check without an MCP client:

python - <<'PY'
import json
from finbrain_mcp.tools.health import health
print(json.dumps(health(), indent=2))
PY

Connect an AI client

No manual start needed: Claude Desktop and VS Code will launch the MCP server for you based on your config. You only need to run finbrain-mcp yourself for quick sanity checks or debugging.

Claude Desktop

Edit your config:

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Linux: ~/.config/Claude/claude_desktop_config.json

Pip install (published package):

{
  "mcpServers": {
    "finbrain": {
      "command": "finbrain-mcp",
      "env": { "FINBRAIN_API_KEY": "YOUR_KEY" }
    }
  }
}

macOS tip (full path):

If "command": "finbrain-mcp" doesn’t work, find the absolute path and use that instead.

which finbrain-mcp    # macOS/Linux
# (Windows: where finbrain-mcp)

Claude config with full path (macOS example):

{
  "mcpServers": {
    "finbrain": {
      "command": "/full/path/to/finbrain-mcp",
      "env": { "FINBRAIN_API_KEY": "YOUR_KEY" }
    }
  }
}

Dev venv (run the module explicitly):

{
  "mcpServers": {
    "finbrain-dev": {
      "command": "C:\\Users\\you\\path\\to\\repo\\.venv\\Scripts\\python.exe",
      "args": ["-m", "finbrain_mcp.server"],
      "env": { "FINBRAIN_API_KEY": "YOUR_KEY" }
    }
  }
}

Docker:

{
  "mcpServers": {
    "finbrain": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "finbrain-mcp:latest"],
      "env": { "FINBRAIN_API_KEY": "YOUR_KEY" }
    }
  }
}

After editing, quit & reopen Claude.

VS Code (MCP)

  1. Open the Command Palette → “MCP: Open User Configuration”.
    This opens your mcp.json (user profile).

  2. Add the server under the servers key:

    {
  "servers": {
    "finbrain": {
      "command": "finbrain-mcp",
      "env": { "FINBRAIN_API_KEY": "YOUR_KEY" }
    }
  }
}

  3. In Copilot Chat, enable Agent Mode to use MCP tools.

What can you ask the agent?

You don’t need to know tool names—just ask in plain English. Examples:

  • Predictions

    • “Get FinBrain’s daily predictions for AMZN.”
    • “Show monthly predictions (12-month horizon) for AMZN.”

  • News sentiment

    • “What’s the news sentiment for AMZN from 2025-01-01 to 2025-03-31 (limit 50)?”
    • “Export AMZN news sentiment for 2025 YTD as CSV.”

  • App ratings

    • “Fetch app store ratings for AMZN between 2025-01-01 and 2025-06-30.”

  • Analyst ratings

    • “List analyst ratings for AMZN in Q1 2025.”

  • Congressional trades

    • "Show recent House trades involving AMZN."
    • "Show recent Senate trades involving META."

  • Insider transactions

    • “Recent insider transactions for AMZN?”

  • LinkedIn metrics

    • “Get LinkedIn employee & follower counts for AMZN (last 12 months).”

  • Options (put/call)

    • “What’s the put/call ratio for AMZN over the last 60 days?”

  • Availability

    • “Which markets are available?”
    • “List tickers in the daily predictions universe.”

Notes

  • Date format: YYYY-MM-DD.
  • Time-series endpoints return the most recent N points by default—say “limit 200” to get more.
  • Predictions horizon: daily (10-day) or monthly (12-month).
  • Say “as CSV” to receive CSV instead of JSON.

Development

# setup
python -m venv .venv
source .venv/bin/activate # Windows: .\.venv\Scripts\activate
pip install -e ".[dev]"  # run tests pytest -q

Project structure (high level)

finbrain-mcp
├─ README.md
├─ pyproject.toml
├─ LICENSE
├─ .github/
├─ examples/
├─ src/
│  └─ finbrain_mcp/
│     ├─ __init__.py
│     ├─ server.py                # MCP server entrypoint
│     ├─ registry.py              # FastMCP instance
│     ├─ client_adapter.py        # wraps finbrain-python; calls normalizers
│     ├─ auth.py                  # resolves API key (env var)
│     ├─ settings.py              # tweakable defaults (e.g., series limits)
│     ├─ utils.py                 # helpers (latest_slice, CSV, DF->records)
│     ├─ normalizers/             # endpoint-specific shapers
│     └─ tools/                   # MCP tool functions (registered & testable)
└─ tests/                         # pytest suite with a fake SDK

Troubleshooting

  • ENOENT (can’t start server)

    • Wrong path in client config. Use the venv’s exact path:

      • …\.venv\Scripts\python.exe + ["-m","finbrain_mcp.server"], or

      • …\.venv\Scripts\finbrain-mcp.exe

  • FinBrain API key not configured

    • Put FINBRAIN_API_KEY in the client’s env block or

    • setx FINBRAIN_API_KEY "YOUR_KEY" and fully restart the client.

  • Mixing dev & prod installs

    • Keep pip (prod) and venv (dev) separate.

    • In configs, point to one or the other—not both.

License

MIT (see LICENSE).

Acknowledgements

  • Built on Model Context Protocol and FastMCP.

  • Uses the official finbrain-python SDK.

© 2025 FinBrain Technologies — Built with ❤️ for the quant community.

Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code
ChatWiseThe second fastest AI chatbot™
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
Tavily Mcp
CursorThe AI Code Editor
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
Howtocook Mcp基于Anduin2017 / HowToCook （程序员在家做饭指南）的mcp server，帮你推荐菜谱、规划膳食，解决“今天吃什么“的世纪难题； Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
Playwright McpPlaywright MCP server
TimeA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
DeepChatYour AI Partner on Desktop
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
Serper MCP ServerA Serper MCP Server
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.
WindsurfThe new purpose-built IDE to harness magic
Baidu Map百度地图核心API现已全面兼容MCP协议，是国内首家兼容MCP协议的地图服务商。
Y GuiA web-based graphical interface for AI chat interactions with support for multiple AI models and MCP (Model Context Protocol) servers.
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
Amap Maps高德地图官方 MCP Server