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.

MCP server

Ship DataSinking to any AI agent (Claude Desktop / Cursor / Codex / Windsurf) as an
MCP server — 6 tools: list exchanges, list stocks,
list reports, fetch a report, list sections, fetch one section (token-friendly for RAG).

pip install "datasinking[mcp]"
datasinking-mcp          # requires DATASINK_API_KEY (free at https://datasink.ing)

Or add to your client with command: datasinking-mcp. A remote streamable-HTTP endpoint
is also live at https://api.datasink.ing/mcp. See mcp-server.md.

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). Quotas count documents, not requests, and apply over a rolling 31-day window as well as per day: a free key gets 3 req/s and 8,191 documents/day, inside a pool of 131,071/day and 524,287 per 31 days shared by all free users. A whole exchange will therefore take more than a day on a free key — a paid (yearly) key (31 req/s, 131,071 documents/day, 524,287 per 31 days) is strongly recommended.

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 the official regulatory disclosure platform of each market and converted in-house to clean Markdown:

Every document also carries a source field in the API response, so the attribution travels with the data. Please keep it when you redistribute.

License

MIT