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edgar-entity-mcp

by pgeneralpl

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    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to research US public company filings, financials, and insider transactions using SEC EDGAR data, with no API keys required. Provides tools for company lookup, recent filings, full-text search, financial facts, and insider activity.
      5
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables corporate disclosure research through official SEC EDGAR and GLEIF sources, providing tools for company resolution, filings, insiders, ownership, financials, and private raises via natural language.
      51 npm
      2
      Apache 2.0
    • F
      license
      A
      quality
      D
      maintenance
      Provides access to SEC filings and detailed XBRL financial data for all publicly traded U.S. companies. It enables users to search for company info, retrieve historical metrics like revenue and assets, and compare financial performance across different industries.
      6
      1
      -
    • A
      license
      A
      quality
      B
      maintenance
      Query SEC EDGAR for company filings, financial data, and executive disclosures. Search by company name or ticker, retrieve 10-K/10-Q/8-K filings, and extract structured financials — backed by the official SEC EDGAR API, built for AI agents.
      4
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Give your AI agent live SEC EDGAR data: company financials, insider trades, 8-K events, 13F holdings, and the raw filings stream — all normalized to clean JSON, every number traceable back to its sec.gov source filing.
      8
      49 PyPI
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to query US public company financial data from SEC filings, with tools for resolving tickers, listing filings, retrieving financial concepts, comparing companies, extracting filing sections, and full-text search. It surfaces data ambiguities like tag variations, restatements, and fiscal-year misalignment rather than hiding them.
      6
      MIT

    TDQS

    A4.4/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool targets a distinct resource and action: company search vs. profile, filing listing vs. primary-document retrieval, normalized financials vs. arbitrary XBRL concepts vs. cross-company comparison, insider trades, and state registry lookup. Overlap among the financial tools is explicitly resolved in the descriptions (e.g., use get_xbrl_concept for tags not covered by get_financials).

    Naming Consistency5/5

    All tool names use snake_case with a predictable verb_noun structure (search_company, get_company_profile, list_filings, get_financials, etc.). Verb variety appropriately matches the operation without introducing stylistic inconsistency.

    Tool Count5/5

    The set contains 10 tools, well within the ideal range for a focused research server. Each tool covers a distinct part of the SEC/entity research workflow, with no obvious redundancy or thinness.

    Completeness4/5

    Core company research is well covered: discovery, profile, filings, primary documents, financials, XBRL concepts, comparisons, insider trades, and state registry lookup. Minor gaps remain for non-primary filing exhibits and institutional ownership/13F data, though agents can work around most needs.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues