Full-text Asian financial reports (China, Japan, Korea, Taiwan) as clean Markdown — REST API + MCP server for LLMs, RAG and quant
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
claude mcp add datasinking -- python -m datasinking{
"mcpServers": {
"datasinking": {
"command": "python",
"args": ["-m", "datasinking"]
}
}
}Resumen de MCP Servers
# DataSinking
<!-- mcp-name: io.github.heubme2020/datasinking -->
[](https://pypi.org/project/datasinking/)
[](https://github.com/heubme2020/datasinking#mcp-server)
**Full-text financial reports across Asia, as clean Markdown.**
[DataSinking](https://datasink.ing) serves **full-text financial reports** — annual, semi-annual
and quarterly — from **China, Korea, Japan and Taiwan** as clean **Markdown**, ready for LLM reading
and RAG. Query by FMP-style symbol (`600519.SS`, `005930.KS`, `7203.T`, `2330.TW`) 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 / Cursor / Codex / Windsurf) as an
[MCP](https://modelcontextprotocol.io) server — 6 tools: list exchanges, list stocks,
list reports, fetch a report, list sections, fetch one section (token-friendly for RAG).
### Hosted — nothing to install
Point any MCP client at our endpoint and you're done. No package, no Python, no local server:
```json
{
"mcpServers": {
"datasinking": {
"type": "http",
"url": "https://api.datasink.ing/mcp?apikey=YOUR_KEY"
}
}
}
```
Claude Code, in one line:
```bash
claude mcp add --transport http datasinking https://api.datasink.ing/mcp \
--header "Authorization: Bearer YOUR_KEY"
```
Your key rides inside the URL, so treat that config as a secret. Clients that support custom
headers can send `Authorization: Bearer YOUR_KEY` instead — Claude Code redacts headers in its
output but can't redact a URL.
### Local — run it yourself
If you'd rather keep everything on your own machine:
```bash
pip install "datasinking[mcp]"
datasinking-mcp # requires DATASINK_API_KEY (free at https://datasink.ing)
```
Then use `command: datasinking-mcp` in your client.
Full per-client setup: [`mcp-server.md`](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](https://datasink.ing)
2. One line (FMP-style `?apikey=`):
```bash
curl "https://api.datasink.ing/documents?symbol=600519.SS&with_content=1&apikey=YOUR_KEY"
```
Or in Python:
```bash
pip install datasinking
```
```python
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`](api-examples.md).
## Ask an LLM (no code)
Don't want to write code? Point any LLM at [datasink.ing](https://datasink.ing),
give it your API key, and ask in plain language. See
[`llm-examples.md`](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). Quotas count **documents, not requests**, over a rolling 7-day window: a free key gets 3 req/s and 8,191 documents per 7 days, inside a pool of 524,287 per 7 days shared by all free users and website visitors. A whole exchange will therefore take well over a week on a free key — a **paid (yearly)** key (31 req/s, 524,287 documents per 7 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`](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](LICENSE)
Lo que la gente pregunta sobre datasinking
¿Qué es heubme2020/datasinking?
+
heubme2020/datasinking es mcp servers para el ecosistema de Claude AI. Full-text Asian financial reports (China, Japan, Korea, Taiwan) as clean Markdown — REST API + MCP server for LLMs, RAG and quant Tiene 16 estrellas en GitHub y su última actualización registrada es del 2026-09-22.
¿Cómo se instala datasinking?
+
Puedes instalar datasinking clonando el repositorio (https://github.com/heubme2020/datasinking) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar heubme2020/datasinking?
+
Nuestro agente de seguridad ha analizado heubme2020/datasinking y le ha asignado un Trust Score de 95/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene heubme2020/datasinking?
+
heubme2020/datasinking es mantenido por heubme2020. La última actividad registrada en GitHub es del 2026-09-22, con 0 issues abiertos.
¿Hay alternativas a datasinking?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
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