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edgar-search-mcp

edgar-search-mcp

by jibarix

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    • A
      license
      A
      quality
      B
      maintenance
      Provides access to SEC EDGAR financial data, enabling AI agents to fetch company filings, financial metrics, and narrative sections. It supports natural-language metric searching and extracts structured data from 10-K, 10-Q, and 8-K reports.
      6
      45 PyPI
      MIT
    • 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
      1
      MIT
    • 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
      B
      maintenance
      Provides 22 read-only tools that let AI assistants pull and read SEC EDGAR data straight from official sec.gov APIs: 10-K, 10-Q, 8-K, 20-F and proxy filings, paged or phrase-searched filing text, XBRL facts and cross-company rankings, insider trades, 13D/13G ownership and 13F portfolios. Also enables full-text search across every EDGAR filing since 2001, so users can answer company financial questions in natural language without an API key.
      22
      67 PyPI
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables querying of SEC EDGAR filings and financial data via natural language, offering tools for company lookup, filing retrieval, XBRL data, and full-text search.
      154 npm
      MIT

    TDQS

    A4/5.0

    Scored across 11 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes: company lookup, submissions, facts, frames, filing listing, document retrieval, XBRL parsing, text extraction, and full-text search are separable. There is some overlap between get_companyfacts (which can filter by concept) and get_companyconcept, and between raw document retrieval and text extraction, though the descriptions make the distinctions mostly usable.

    Naming Consistency5/5

    All tools use snake_case and follow a predictable verb_noun pattern: lookup_company, get_submissions, get_companyfacts, list_filings, search_filings, and so on. The verbs are natural and consistent enough for an agent to infer behavior from names.

    Tool Count5/5

    Eleven tools is well within a reasonable range for an SEC EDGAR access server. Each tool maps to a meaningful read-only capability, and there are no obviously redundant filler tools.

    Completeness4/5

    The surface covers company lookup, submissions, facts, concepts, frames, filing lists, filing documents, XBRL, text extraction, and full-text filing search, which is broad coverage for the domain. Minor gaps include limited company discovery beyond exact CIK/ticker/title matching and no obvious cross-company filing browse operation outside search.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues