A comprehensive financial intelligence platform providing 200+ data modules as a free, open-source alternative to the Bloomberg Terminal.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quantclaw-data
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install quantclaw-data using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is QuantClaw Data?
QuantClaw Data is a massive financial intelligence engine designed to provide institutional-grade data through a flexible architecture. As a core part of the Openclaw Skills library, it bridges the gap between raw financial markets and AI agents, offering over 140,000 lines of code dedicated to market analysis, quantitative modeling, and alternative data ingestion.
The platform democratizes access to expensive financial datasets by aggregating 187 unique sources like FRED, SEC EDGAR, and Yahoo Finance. Whether you are building an automated trading bot or a research assistant, this skill provides the necessary endpoints for real-time prices, technical indicators, and complex simulations without requiring expensive API keys for its core features.
QuantClaw Data Use Cases
- High-frequency technical analysis and stock screening for specific sectors or market caps.
- Quantitative research including Monte Carlo simulations, Fama-French factor modeling, and Kalman filters.
- Monitoring macro-economic indicators such as yield curves, inflation rates, and Fed policy.
- Tracking alternative data like dark pool activity, insider trading, and sentiment analysis from SEC filings.
- Building multi-asset dashboards covering Crypto, FX, and Commodities within the Openclaw Skills ecosystem.
How QuantClaw Data Works
- The user interacts with the skill via one of three interfaces: a CLI for local scripts, a REST API for web applications, or a Model Context Protocol (MCP) server for AI agents.
- Upon a request (e.g., fetching technicals), the system routes the query through one of its 175 Python modules.
- The module fetches raw data from one or more of the 187 integrated sources, bypassing the need for individual API keys where possible.
- Data is processed, normalized, and enriched with analytical insights like Greeks for options or sentiment scores for news.
- The refined financial intelligence is returned to the user or agent in a structured format for immediate decision-making.
QuantClaw Data Setup
To integrate this into your environment, follow these steps to install the required Openclaw Skills dependencies:
# Clone the repository
git clone https://github.com/yoniassia/quantclaw-data.git
cd quantclaw-data
# Install the necessary Python environment
pip install yfinance numpy scipy pandas statsmodels pandas-datareader requests beautifulsoup4
For MCP users, add the following to your configuration file:
{
"mcpServers": {
"quantclaw-data": {
"command": "node",
"args": ["mcp-server.js"],
"cwd": "/path/to/quantclaw-data"
}
}
}
QuantClaw Data Data Schema & Taxonomy
QuantClaw Data organizes its vast library into specific functional categories to ensure high discoverability within Openclaw Skills:
| Category | Focus Area | Data Examples |
|---|---|---|
| Core Market | Equity basics | Prices, profiles, and sector screeners |
| Derivatives | Options & Vol | GEX, volatility surfaces, and Greeks |
| Quantitative | Advanced Math | Fama-French, Monte Carlo, and pairs trading |
| Alternative | Non-traditional | Satellite imagery, sentiment, and dark pools |
| Fixed Income | Macro | Yield curves, CDS, and central bank policies |
QuantClaw Data Advanced Features
- Support for 210 MCP tools, allowing AI agents to call financial functions autonomously.
- Built-in NLP capabilities for analyzing earnings call transcripts and SEC filing sentiment.
- Infrastructure for automated backtesting and reconciliation of trading strategies.
- Cross-asset intelligence spanning traditional finance, DeFi, and global commodities.
- 54 Next.js API routes for seamless integration into custom web dashboards.
SKILL.md
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