dart-risk-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables investors and analysts to query Korean listed companies' financial health, accounting risks, and disclosure events using DART filings, accessible via natural language through Claude.2Apache 2.0
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- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to query Korea's OpenDART disclosure system, covering filings, financials, ownership, and XBRL with Buffett-style quality checklists, insider signals, and accounting risk scoring, plus conversion of HWP/PDF attachments into markdown for direct analysis.1,087 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to search and analyze Korean OpenDART electronic disclosures, financial statements, equity filings, and XBRL data through a compressed set of enum-based tools, including insider-trading cluster signals, 0-100 accounting risk scoring, and Buffett-style quality checklists. It also converts DART XML and HWP/PDF report attachments into readable markdown for direct document analysis.1,087 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to search Korean DART electronic disclosures, retrieve financial statements and fully parsed XBRL with calculation checks, and run analyst-style frames such as insider buy/sell cluster signals, 0-100 accounting risk scoring, and Buffett quality checklists. It also converts HWP/PDF filing attachments into markdown for direct reading and summarization.1,087 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants to query Korean OpenDART electronic disclosure data — disclosures, financials, equity, and XBRL — through 15 consolidated tools, including insider-trading signals, accounting-risk scoring, Buffett-style quality checklists, and HWP/PDF attachment-to-Markdown conversion.1,087 npmMIT
TDQS
Scored across 35 tools
Most tools carve out distinct scopes and the descriptions explicitly cross-reference neighbours (get_financial_summary vs get_financial_statements_full vs compare_financials; get_audit_opinion_history vs get_audit_opinion_text; get_disclosure_document vs list_disclosure_sections vs view_disclosure). The risk cluster is the soft spot: analyze_company_risk, check_disclosure_anomaly, build_event_timeline and find_risk_precedents all produce 'risk signal' output, and an agent could plausibly pick the wrong one for a given question. get_shareholder_info vs track_insider_trading also overlap on ownership data (snapshot vs time series).
All 35 names are snake_case verb_noun (find_, get_, check_, list_, view_, search_, track_, scan_, build_, lookup_, manage_, compare_). Verb variety (track_/scan_/build_) tracks meaningful differences in behavior rather than ad-hoc style drift, and no camelCase or bare-noun names appear.
35 tools is well past the heavy threshold, and several clusters could be consolidated (three disclosure-reading tools, four financial-statement tools, four risk/scoring-style tools, two audit tools). The domain breadth is genuine — disclosures, financials, capital events, audit, market scan, watchlist — but the count forces agents to search a long list and increases selection error.
Coverage is unusually deep for the stated purpose: CRUD-ish disclosure retrieval, financials at multiple granularities, capital structure and mezzanine terms, audit history plus quoted text, ownership/insider data, market-wide scanning, market reaction, and unlisted-company financials. Remaining gaps are modest: no free-text disclosure-title search across a company (only presets and singled-out report_name), no consolidated group/ownership-graph view, and find_risk_precedents exposes a lookback_days arg that is documented as unused.