DataSinking

MCP serverDocs & knowledge

Lets your agent read full-text financial reports from the US, China, Japan, Korea and Taiwan as clean Markdown.

Use DataSinking in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add DataSinking and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use DataSinking

Details

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

DataSinkingStart free
About this server

Full-text financial reports (US, China, Japan, Korea, Taiwan) as clean Markdown for RAG agents.

Install DataSinking

The server’s own address, for the clients that take one directly. Or connect ahel once and every client you use reads it from one address, with the account kept on ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http --scope user datasinking 'https://api.datasink.ing/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

    https://api.datasink.ing/mcp

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=datasinking&config=eyJ1cmwiOiJodHRwczovL2FwaS5kYXRhc2luay5pbmcvbWNwIn0=

    Open the link and Cursor adds the server at that address.

  • ChatGPT

    https://api.datasink.ing/mcp

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add datasinking --url 'https://api.datasink.ing/mcp'

    Run it once, then sign in with codex mcp login datasinking if the server asks for an account.

From the project's README

As published by heubme2020/datasinking in README.md.

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/)

FileWhat it does
01_quickstart.pyThe 5 core functions: list exchanges / stocks / reports / fetch a report / fetch a stock's reports
02_download_company.pyDownload a company's full reports to local Markdown files
03_download_exchange.pyDownload 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). 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

CoverageChina (SSE / SZSE / BSE) · Korea (KOSPI / KOSDAQ / KONEX) · Japan (TSE) · Taiwan (TWSE / TPEx)
Document typesannual / semiannual / q1 / q3 / amendment
Update frequencyDaily — Korea/Japan via official DART/EDINET APIs (new filings within ~24h of publication)
FormatFull-text Markdown (with YAML frontmatter)
APIREST — GET /documents, batch download, with_content=1 for full text, ?section= + /sections for chapter-level access
SymbolsFMP 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:

MarketSourcePlatform
China A-shares (.SS .SZ .BJ)巨潮资讯网 cninfoCSRC-designated disclosure platform
Korea (.KS .KQ .KN)DARTFinancial Supervisory Service — opendart.fss.or.kr
Japan (.T)EDINETFinancial Services Agency — disclosure2.edinet-fsa.go.jp
Taiwan (.TW .TWO)公開資訊觀測站 MOPSTaiwan 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

Signals

GitHub stars
19
Forks
3
Last commit
Sep 2026
Weekly downloads
266
Weekly_downloads
270 weekly_downloads
Advanced
Delivery
datasinking MCP server → your ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-heubme2020-datasinking
Source
github.com/heubme2020/datasinking
Hosted endpoint
https://api.datasink.ing/mcp