Skip to content

DAAS - Data As a Service

Skill-driven data fetch for financial, economic, and statistical data - a local platform that turns Python data libraries (akshare, yfinance, edgar, edinet-tools, dartlab, world_bank_data, ckanapi) into a queryable, indicator-computing, dashboard-ready store backed by a single SQLite file (daas.db).

You can drive DAAS through Claude Code skills or through a consolidated MCP server - both paths read/write the same database.

What you can do

  • Browse thousands of indicators across companies, industries, cities, and countries - moving averages, RSI, volatility, macro series, and more.
  • Build collections - group entities (a watchlist) and indicators (a reusable bundle) with audit-tracked membership.
  • Run a research - from a goal to a persisted bundle: analyze -> collections -> indicators -> dashboard -> markdown report.
  • Inspect any entity - see which datasources cover a stock/country and how to fetch them.
  • Extract & analyze financial reports - pull filings (EDGAR/EDINET/DART) and compute dozens of prebuilt indicators on top.
  • Add your own datasource - a website, a PDF/document, or a database - and query it like the built-ins.
  • Share a dashboard - publish a standalone HTML dashboard over WiFi/LAN or a public tunnel.

Two ways to use it

Path When to use
Skills (.claude/skills/) Offline-friendly, simplest. Skills call Python libs directly + sqlite3.
MCP server (fd-daas-mcp) Richer - catalog browsing, cron, alerts, dashboards, orchestration, PDF search.

Both share one daas.db. See Concepts -> Entities for the data model, or jump to the Examples.

Where to start

This site vs. the repo README

The repo-root README.md is a verified quickstart. This site is the teachable, role-based guide - start here, use the README for copy-paste commands.