DataSinking

Full-text financial reports across Asia, as clean Markdown.

DataSinking serves full-text financial reports — annual, semi-annual and quarterly — from China, Korea and Japan as clean Markdown, ready for LLM reading and RAG. Query by FMP-style symbol (600519.SS, 005930.KS, 7203.T) or filter by exchange, report period, or section — pull just the MD&A / risk section instead of the whole report. Reports are sourced from official disclosure platforms and parsed into structured Markdown with YAML frontmatter, preserved headings, paragraphs and tables.

What this repo is

Examples, research and tutorials showing how to work with financial report data, including reproducing the presentation styles found in financial-report research papers.

datasinking/
├── examples/     # Example scripts: pull data from the API and analyze it
├── research/     # Research notes / blog posts (reproducing paper-style presentation)
├── datasinking/  # Python client + MCP server — pip install "datasinking[mcp]"
├── mcp-server.md # How to configure the MCP server (for AI agents: Claude / Cursor / Codex / DeepSeek)
├── llm-examples.md  # Ask an LLM — no code needed (8 end-to-end examples)
├── api-examples.md  # 7 examples × 3 interfaces (curl / Python / LLM)
└── README.md

Quick start

1. Get an API key at datasink.ing
2. One line (FMP-style ?apikey=):

curl "https://api.datasink.ing/documents?symbol=600519.SS&with_content=1&apikey=YOUR_KEY"

Or in Python:

pip install datasinking

from datasinking import DataSinking

ds = DataSinking("YOUR_KEY")
for r in ds.get_stock_reports("600519.SS", limit=3):
    print(r["report_period"], r["title"], len(r["content"]), "chars")

All five functions (curl / Python / LLM): api-examples.md.

Ask an LLM (no code)

Don't want to write code? Point any LLM at datasink.ing, give it your API key, and ask in plain language. See llm-examples.md for eight end-to-end examples — explore coverage, list a company's reports, and extract a figure with correct units.

Examples (examples/)

Every example pulls from the live API and runs as-is.

03_download_exchange.py fetches every report on an exchange (e.g. all of Shenzhen — 150k+ documents). Free keys work too, but fall back to slow per-document fetching (1 req/s + shared daily quota); a paid (yearly) key is strongly recommended for full-exchange downloads.

Research (research/)

research/ hosts research notes and blog posts, each based on DataSinking data with the source cited. You can reproduce charts and presentations found in financial-report research papers, e.g.:

• Long-term revenue / profit trends
• Industry comparison and distribution
• Time series of financial metrics

Start from research/TEMPLATE.md.

Data overview

Data source

Reports are sourced from official regulatory disclosure platforms in each market and converted in-house to clean Markdown.

License

MIT