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DataSinking

PyPI version MCP server

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.

DataSinking MCP in Claude

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/)

File What it does
01_quickstart.py The 5 core functions: list exchanges / stocks / reports / fetch a report / fetch a stock's reports
02_download_company.py Download a company's full reports to local Markdown files
03_download_exchange.py Download an entire exchange's reports (all stocks) to local Markdown files

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 (3 req/s, 8,191 requests/day per key, drawn from a 131,071/day pool shared by all free users); 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

Coverage China (SSE / SZSE / BSE) · Korea (KOSPI / KOSDAQ / KONEX) · Japan (TSE) · Taiwan (TWSE / TPEx)
Document types annual / semiannual / q1 / q3 / amendment
Update frequency Daily — Korea/Japan via official DART/EDINET APIs (new filings within ~24h of publication)
Format Full-text Markdown (with YAML frontmatter)
API REST — GET /documents, batch download, with_content=1 for full text, ?section= + /sections for chapter-level access
Symbols FMP style: 600519.SS / 005930.KS / 7203.T
Auth ?apikey= query parameter (FMP style)

Data source

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

Market Source Platform
China A-shares (.SS .SZ .BJ) 巨潮资讯网 cninfo CSRC-designated disclosure platform
Korea (.KS .KQ .KN) DART Financial Supervisory Service — opendart.fss.or.kr
Japan (.T) EDINET Financial Services Agency — disclosure2.edinet-fsa.go.jp
Taiwan (.TW .TWO) 公開資訊觀測站 MOPS Taiwan Stock Exchange — mops.twse.com.tw

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

Metadata

Release files for datasinking 0.2.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Table of built distributions (wheels) for datasinking 0.2.3
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datasinking-0.2.3-py3-none-any.whl Python 3 none any Details

Total release size: 19.8 kB

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