DataSinking

Full-text financial reports across the US, Europe and Asia, as clean Markdown.

DataSinking serves full-text financial reports — annual, semi-annual and quarterly — from the US, China, Europe, Japan, Korea and Taiwan as clean Markdown, ready for LLM reading and RAG. Query by FMP-style symbol (AAPL, 600519.SS, 7203.T, 005930.KS, 2330.TW) or filter by exchange, report period, or section — pull just the MD&A / risk section instead of the whole filing, saving tokens. Every figure is traceable to its source disclosure and block. 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 / Devin Desktop / n8n) as an MCP server — 8 tools: list exchanges, list stocks, list reports, fetch a report, list sections, fetch one section (token-friendly for RAG), request a full backfill of a stock (idempotent — returns the current status if already queued), check a backfill's progress.

Hosted — nothing to install

One URL, no package, no Python, no local server. Most clients take this shape:

{
  "mcpServers": {
    "datasinking": {
      "type": "http",
      "url": "https://api.datasink.ing/mcp",
      "headers": { "Authorization": "Bearer YOUR_KEY" }
    }
  }
}

Claude Code, in one line:

claude mcp add --transport http datasinking https://api.datasink.ing/mcp \
  --header "Authorization: Bearer YOUR_KEY"

A client that can't set a header can put the key in the URL instead — https://api.datasink.ing/mcp?apikey=YOUR_KEY — but only do that when you must: a key in a URL ends up in logs and screen shares, and no client can redact it.

Two clients don't fit the shape above: Codex's config is TOML, and Devin Desktop's remote field is serverUrl, not url. Per-client files: docs/mcp/.

Local — run it yourself

If you'd rather keep everything on your own machine, there are two identical builds — pick whichever runtime you already have:

Node 18+ (no Python needed):

{
  "mcpServers": {
    "datasinking": {
      "command": "npx",
      "args": ["-y", "datasinking-mcp"],
      "env": { "DATASINK_API_KEY": "YOUR_KEY" }
    }
  }
}

Python 3.8+:

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

Then use command: datasinking-mcp in your client.

Both run the same eight tools with the same schemas — npm/ and datasinking/mcp_server.py are kept in lockstep by check_mcp_parity.py.

Full per-client setup: mcp-server.md (overview) · docs/mcp/ (one guide per client).

The hosted endpoint is POST-only and stateless — GET /mcp returns 405, and no session id is issued. Most clients read MCP config at launch, so restart one after changing its config.

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]"
├── npm/          # The same MCP server on npm — npx -y datasinking-mcp (Node 18+)
├── r-datasinking/  # R client — remotes::install_github("heubme2020/

... [View full README on GitHub](https://github.com/heubme2020/datasinking#readme)