Mrbaeksang/korea-stock-analyzer-mcp

Description and use

**Brief Summary (2‑3 sentences)**
Mrbaeksang/korea‑stock‑analyzer‑mcp is a remote Model‑Context‑Protocol (MCP) server that delivers real‑time Korean market data—including DART filings, KRX quotes, and conservative valuation ranges—to any MCP‑compatible AI assistant (Claude, Cursor, etc.). By exposing a clean API/SDK/CLI in Python, it lets developers plug AI agents into authentic financial tools without building custom scrapers or parsers. The project is actively maintained, has modest community traction, and is positioned as a production‑ready OSS component for AI‑driven stock analysis.

**Value**

• **Real‑world data for LLMs** – Provides trustworthy, up‑to‑date regulatory filings and market quotes, turning generic language models into domain‑aware financial analysts.
• **Standardized integration** – Implements the Model‑Context‑Protocol, so the same server can be consumed by any MCP‑compatible client, reducing duplicate integration work across AI platforms.
• **Conservative valuation logic** – Supplies pre‑computed valuation ranges, giving agents a safe baseline for recommendations and mitigating hallucination risk.

**Practical Adoption Path**

1. **Spin up the server** – Clone the repo, install the Python dependencies, and run the Docker compose or the provided CLI to launch the MCP endpoint.
2. **Configure your AI client** – In Claude, Cursor, or any custom MCP client, point the mcp_endpoint to the server URL and authenticate if required.
3. **Consume the API** – Use the documented RPC methods (e.g., get_dart_filing, get_krx_quote, get_valuation_range) to fetch data inside prompts or tool‑use calls.
4. **Extend / customize** – Add new data sources or tweak valuation formulas by modifying the Python modules and redeploying; the open‑source nature makes this straightforward.

**Production Readiness**

• **Recent activity** – Last commit on 2026‑07‑08, 21 stars, 9 forks, and active issue discussion indicate a healthy maintainer presence.
• **Robust interface** – Offers API, SDK, and CLI bindings, with clear OpenAPI‑style docs, facilitating automated testing and CI/CD integration.
• **Ecosystem fit** – Built in Python, a language widely used for AI pipelines, and already referenced in MCP tooling guides, lowering the learning curve for teams.
• **Risk considerations** – License and security posture need a final audit, but no glaring metadata issues are present. Overall, the project is mature enough for a pilot or production deployment, provided standard OSS due‑diligence steps are followed.

Use in a workflow

Mrbaeksang/korea-stock-analyzer-mcp helps connect AI assistants to real tools and data through a standard protocol.

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Limitations and review notes

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.