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Compare scores, permissions, risks, and fit in one decision-focused table.

DimensionDartLabKorean DART + US SEC EDGAR filings as structured Python data for company analysis.NPM Sentinel MCP ServerAI-powered NPM package analysis MCP server
FMRS58 / 100 · C79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions12 / 2016 / 20
Maintenance14 / 2018 / 20
Documentation12 / 2018 / 20
Setup experience12 / 2015 / 20
Best for
  • Quantitative analysts and investors with deep research needs in the Korean stock market (KOSPI/KOSDAQ).
  • Developers needing structured financial data in Python environments.
  • Those who want to integrate financial analysis capabilities into AI assistants like Claude or Codex via MCP.
  • Developers auditing NPM dependencies within AI workflows
  • Teams performing supply chain security assessments
  • Users of Claude Desktop, Cursor, or VS Code
Not for
  • Those needing real-time stock price or high-frequency trading data (data is prebuilt, potentially with some latency).
  • Those focused only on US small-cap companies or deep EDGAR data (EDGAR support is limited).
  • Users seeking a lightweight, single-purpose data source (it's feature-rich but heavy).
  • Projects outside the NPM ecosystem (e.g., pure Python/Go)
  • Environments without network access to deps.dev, OSV.dev, and the npm registry
  • Scenarios requiring maintenance by an official upstream vendor
Required permissions
  • Network access to download prebuilt data from HuggingFace, and access to DART and SEC APIs (EDGAR).
  • Local file system permissions for caching data (default in user directory).
  • For MCP configuration, need to modify config files for Claude Desktop or CLI.
  • Optional: DART API key (for raw data re-collection, not needed for regular use).
  • Network access to the NPM registry and external services (deps.dev, OSV.dev, OpenSSF, npms.io, GitHub)
  • Read access to workspace lockfiles (pnpm-lock.yaml, package-lock., yarn.lock) for cache invalidation
Risks and side effects
  • External disclosure content (e.g., news, filings) may be wrapped as untrusted when serialized, but AI should use it only as analysis basis, not execute any instructions within.
  • Prebuilt data may not be up-to-date; be aware of time lags.
  • When using remote MCP endpoint, ensure stable internet connection.
  • Installation issues could arise if Python path is not set properly, affecting MCP configuration.
  • Third-party READMEs and changelogs are untrusted external content; they are wrapped in tags with _meta flags but should still be handled cautiously
  • Depends on availability and accuracy of external services
  • Batch requests are capped at 25 packages to prevent registry enumeration; larger sets require batching
  • Third-party open source project, not officially maintained by NPM or Anthropic
Supported clientsClaude Desktop, Claude Code, Codex, CursorClaude Desktop, VS Code, Cursor
Tools2219