DartLab is a powerful financial data MCP server designed for Korean DART and US EDGAR disclosure data. It offers rich data interfaces and AI analysis capabilities, suitable for deep financial research. Installation requires pre-installing the Python package and configuring MCP clients. It currently supports Claude Desktop, Claude Code, Codex, and Cursor. Note that it requires significant local disk space and network resources, and provides limited depth for US stocks. Overall, it is an extremely valuable tool for researchers focused on the Korean market.
DartLab is an open-source research system that turns Korean DART and US SEC EDGAR disclosures into comparable corporate data. It provides financial statements, business report full text, filing lists, ratios, credit risk, industry maps, and macro context through a unified Company interface. The core is horizontalizing each company's differing account names and disclosure tables into topic × period and account × period grids, enabling comparisons across years, across companies (e.g., Samsung vs Apple), and across the entire market. The system offers a Python library, CLI, and AI assistant (via MCP) with five analysis lenses (Analysis, Credit, Industry, Quant, Macro), plus scan, screener, story, and simulation features. Data is prebuilt on HuggingFace, and no API keys are required to get started.
Install the Python package: pip install dartlab or uv add dartlab. Then, for Claude Desktop, add an MCP server config in your settings file using command dartlab mcp (pre-install with uv tool install dartlab). For Claude Code, run claude mcp add dartlab -- dartlab mcp. For Codex CLI, run codex mcp add dartlab -- dartlab mcp. You can also connect via remote SSE: https://eddmpython-dartlab.hf.space/mcp/sse (note: Claude Desktop does not support remote endpoints).
{
"mcpServers": {
"dartlab": {
"command": "dartlab",
"args": ["mcp"],
"env": { "PYTHONUNBUFFERED": "1", "PYTHONUTF8": "1" }
}
}
}